Towards understanding exercise adherence in chronic obstructive pulmonary disease Ellen Ricke
Towards understanding exercise adherence in chronic obstructive pulmonary disease Ellen Ricke
© Ellen Ricke, Groningen 2023 No part of this book may be reproduced or transmitted in any form or by any means, without prior permission in writing by the author, or when appropriate, by the publishers of the publications. Cover design: Ellen Ricke Layout: Ellen Ricke Production: IPSKAMP Printing The printing of this thesis was financially supported by the University of Groningen
Towards understanding exercise adherence in chronic obstructive pulmonary disease Proefschrift ter verkrijging van de graad van doctor aan de Rijksuniversiteit Groningen op gezag van de rector magnificus prof. dr. C. Wijmenga en volgens besluit van het College voor Promoties. De openbare verdediging zal plaatsvinden op donderdag 28 september 2023 om 12.45 uur door Ellen Ricke geboren op 18 december 1976 te Amsterdam
Promotor Prof. dr. A. Dijkstra Copromotor Dr. E.W. Bakker Beoordelingscommissie Prof. dr. M.F. Reneman Prof. dr. R. de Vos Prof. dr. C. P. van Wilgen
Paranimfen Anke Dondertman, ervaringsdeskundige Johan Smit, ervaringsdeskundige
Contents Chapter 1 General Introduction 10 Chapter 2 Measuring adherence in clinic-based physiotherapy: a study of the inter-rater reliability of a Dutch measurement. 20 Chapter 3 Measuring adherence to pulmonary rehabilitation: a prospective validation study of the Dutch version of the Rehabilitation Adherence Measure for Athletic Training (RAdMAT-NL). 34 Chapter 4 Prognostic factors of adherence to home-based exercise therapy in patients with chronic diseases: a systematic review and meta-analysis. 56 Chapter 5 Adherence to pulmonary rehabilitation during a 12-month period in Dutch and Flemish patients with prolonged COPD treatment; a prospective cohort study. 84 Chapter 6 Development and validation of a multivariable exercise adherence prediction model for patients with COPD: a prospective cohort study. 100 Chapter 7 Supplement prediction model exercise adherence. 124 Chapter 8 Feasibility, effectiveness and safety of self-management in pulmonary rehabilitation: a study protocol using a hybrid type 1 effectiveness-implementation design. 142 Chapter 9 General discussion 166 Addendum Summary 186 Samenvatting 191 Dankwoord 197 About the author 199
Chapter 1 General introduction
Chapter 1 10 General introduction Healthcare in the Netherlands The prevalence of chronic diseases is rising, triggered by increasing life expectancy and changing lifestyles [1], resulting in an increasing demand for long-term healthcare [2]. This increased demand causes costs to rise, and a shortage of personnel is looming. In the Netherlands, between 2022-2025, healthcare costs will increase by an average of 2.7% per year and annual healthcare employment will grow over the same period with 2.1% [2]. To control rising costs and personnel shortages, the healthcare system needs to transform. The transition in healthcare is evident in the government's vision, which has changed from "care for" to "care that" [3], and the changing view of health as the absence of disease transforming into "the ability to adapt and self-manage in the face of social, physical and emotional challenges” [4]. The focus is on health, behavior and cost savings. The transformation requires a different practice of healthcare, with new roles for patients, for physicians and other healthcare providers, and for health services [5]. Chronic diseases are the most prevalent reason why patients visit physicians, and the reason for 70% of health care expenditures [5]. Chronic diseases are longlasting conditions that usually can be controlled but not cured, so, management over time is essential. To reduce pressure on healthcare and to keep healthcare affordable, chronic disease management should preferably consist of selfmanagement. With more patient self-management, care becomes less laborintensive, which can reduce pressure on healthcare (reducing healthcare utilization) and potentially reduce healthcare costs [5, 6]. To achieve this, patient and healthcare provider must share complementary knowledge and authority in the healthcare process [5]. Patients have to change behaviors to improve symptoms or slow disease progression, with less support of a healthcare provider. This selfmanagement of patients in changing their behavior requires long-term adherence e.g., with regard to an exercise program. Poor adherence to following an exercise program, might lead to many unnecessary health care costs, such as unnecessary additional examinations or unnecessary hospital admissions [7]. Non-adherence is therefore associated with poor treatment outcomes, an increase in complaints, inefficient use of healthcare and an estimated burden of millions per year in avoidable direct healthcare costs [8].The Dutch Ministry of Health, Welfare and Sports (VWS) recognizes that non-adherence is a widespread problem in the Netherlands, and that it affects all kinds of therapy, including physiotherapy, dietary instruction and taking medication [9]. Inadequate adherence to all forms of therapy, results in unnecessary hospitalizations and consultations with general practitioners. Therefore, VWS advises to increase adherence in order to achieve a substantial effect on better quality as well as efficiency of care to be achieved [9].
General introduction 11 Adherence Adherence has been defined as: “the extent to which a person’s behavior in therapeutical interventions, as e.g., the use of medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a health care provider” [10]. Adherence is a complex multi-dimensional construct (patient-related, social/economic, therapy-related, condition-related and health system dimension) [7] that can be indirectly observed through a collection of related events such as attendance at clinic appointments, the extent to which patients follow their prescribed treatment and their communication with their healthcare provider about their recovery in order to provide feedback about their home-based healthcare activities [11]. Non-adherence to appropriately prescribed treatment is a global health problem in healthcare and of relevance to all stakeholders, as described above [7]. Not only society, but especially patients themselves, benefit from adherence. Nonadherence might prevent patients from gaining access and exposure to the best treatment [12], and this may be particularly problematic in chronic conditions, including cardiovascular disease, cancer and chronic obstructive pulmonary disease (COPD) [13]. The number of patients with these chronic diseases is increasing in developed countries [14]. Increasing numbers of patients with chronic diseases are causing greater medical expenses both for society and for the patients themselves [14]. Patients with these common chronic conditions are high utilizers of medical services, have a reduced health related quality of life, experience functional limitations, and are at risk of premature death [13]. These patients also need support to prevent problems from developing and avoid having to manage complications [7]. Physical exercise is in most cases an important aspect of the treatment of chronic diseases [13]. However, many patients often have problems adhering to their prescribed exercise program [15]: 50% of patients with a chronic condition do not adhere to their treatment recommendations [7]. In general, exercise programs that extend over a long duration are more likely to lead to poor adherence [16]. This is because adherence in chronic illness entails a specific pattern of behavior, i.e. performing a behavior over a long period of time to manage the disease as recommended by a healthcare provider [7]. Attention to non-adherence may have a far greater impact on the health of patients with chronic diseases, specifically in patients with COPD [17], than any improvement in specific medical and paramedical treatments [12]. The most effective treatment will be of little use to patients if they have insufficient motivation and competences to adhere to the treatment [18]. When patients adhere to evidence-based interventions, such as, e.g., pulmonary rehabilitation (PR) , this may result in more effective treatments [7].
Chapter 1 12 Adherence measures To improve adherence, it must be measurable. Adherence in patients with chronic diseases entails a specific pattern of behavior (performing a behavior over a long period of time to manage the disease), this leads to one of the problems in studying adherence, namely obtaining accurate measures of adherence behaviors [19]. In addition, people with chronic diseases often have different treatments with different healthcare providers. These healthcare providers come from a wide variety of backgrounds and training e.g., doctors, pharmacists, psychologists, physiotherapists, dieticians, and will approach the problem of adherence from different perspectives [19]. The basis for these differences lies in the fact that there is no consensus on how adherence should be defined and measured [20]. Self-report diaries are the most commonly used measure of adherence, so far. However, there is no standardized diary that can be used across research studies, meaning results are not easily comparable between studies. In addition, poor completion rates for diaries, together with inaccurate recall and self-presentation bias, may further affect validity of these data [21]. More objective is the use of electronic devices such as accelerometers and pedometers [22]. However, these require the patient to use them systematically, and therefore they might only be successful for more adherent patients. Furthermore, electronic devices might not be able to register all prescribed exercises [23]. As there is no reference standard for measuring exercise adherence, no recommendations are currently made from the literature for a specific instrument to measure adherence [12]. So, the availability of a valid and reliable instrument to measure adherence is necessary to make it possible to use a patient-specific intervention and thereby improve the quality of life and health outcomes for patients with chronic diseases and reduce healthcare costs [7]. In addition, it becomes possible to compare results in different settings and under different circumstances [20]. In the literature several measures have been identified to objectify adherence in musculoskeletal disorders. These measures are all unidimensional instruments; they measure one part of a multi-dimensional concept [24]. Only one multidimensional instrument that captures the diverse behaviors that contribute to clinicbased adherence, has been described to measure adherence in a rehabilitation setting: the Rehabilitation Adherence Measure for Athletic Training [25]. The RAdMAT is considered to be reliable, valid, responsive and interpretable at an individual level, easy and simple to use, and low in financial costs [26] in patients with musculoskeletal complaints who are visiting a primary physiotherapy practice. A Dutch version of the RAdMAT could potentially be an appropriate measurement
General introduction 13 instrument to assess adherence in patients with chronic diseases following rehabilitation. If adherence can be measured objectively, it would then be of added value if the probability of adherence could also be predicted. This would enable health care providers to discriminate between adherent and non-adherent patients. Based on this, it can be determined whether someone is capable of more self-management or whether adherence needs to be increased first. The question here is whether adherence actually influences self-management in a positive way. Study population in this thesis Despite substantial progress in reducing the global impact of many chronic diseases, including heart disease and cancer [27], morbidity and mortality due to chronic respiratory disease continues to increase. This increase is driven primarily by the growing burden of chronic obstructive pulmonary disease (COPD) [27]. The prevalence of COPD increased by almost 40% between 1990 and 2017, and by 2017 COPD had become the third leading cause of death globally [27]. Based on demographic trends, the absolute number of patients with COPD is expected to increase by 31% between 2015 and 2040 in the Netherlands [28]. Given the increase in the expected number of patients with COPD, the morbidity and mortality of the disease, the lack of awareness for COPD [29], and the great pressure the disease puts on the healthcare system, patients with COPD were chosen as study population in this thesis (which does not alter the fact that the topic of this thesis is applicable to patients with all kind of chronic diseases). More specifically, people with COPD attending pulmonary rehabilitation for at least one month were chosen. Patients already attending pulmonary rehabilitation understand what is expected of them regarding a more active lifestyle, and they are therefore ideally suited for more focus on self-management with an emphasis on adherence. Interdisciplinary nature of the thesis The content of this thesis is interdisciplinary in nature. Background of pathology and physiology of COPD is the starting point, complemented by physiotherapeutic knowledge regarding pulmonary rehabilitation. In the development of the intervention (the PATCH tool) epidemiological knowledge and knowledge of behavior and psychology come together.
Chapter 1 14 Objectives Based on the gap and challenges identified above, the aim of this thesis is threefold: 1. To develop and validate a measurement instrument to objectively measure exercise adherence in patients with COPD; 2. To develop a prediction model to predict the probability of adherence in patients with COPD already following pulmonary rehabilitation in primary care; and 3. To develop a protocol to investigate the effectiveness of more self-management and the predictive validity of the prediction model. Research questions 1. What is the reliability of a Dutch version of the RAdMAT in patients who are undertaking physiotherapeutic rehabilitation in a primary physiotherapy practice? 2. Wat is the structural and construct validity of a Dutch version of the RAdMAT in patients with chronic obstructive pulmonary disease? 3. What are prognostic factors of home-based exercise adherence in patients with chronic diseases? 4. Is adherence constant over time, or does it rather increase or decrease or fluctuate? 5. What factors predict exercise adherence in patients with COPD following pulmonary rehabilitation? 6. What interventions might possibly improve exercise adherence? 7. What is the effectiveness of more self-management in pulmonary rehabilitation? 8. What is the predictive validity of the PATCH tool used in primary physiotherapy practices? Thesis outline Chapter 2 describes the results of a cross-sectional study, performed to evaluate the inter-rater reliability of the Dutch version of the Rehabilitation Adherence Measure for Athletic Training (RAdMAT-NL). This study forms the basis of the development of a measurement instrument to assess exercise adherence in patients with chronic diseases. Chapter 3 explores the dimensionality and construct validity of the RAdMAT-NL in patients with chronic obstructive pulmonary disease (COPD), using a prospective cohort design. In addition, it examines if the RAdMAT-NL could be used as a single
General introduction 15 score representative of adherence. This study developed a valid and reliable measurement instrument which will be used in the other studies to objectively measure exercise adherence. Chapter 4 sets the basis for the development of an exercise adherence prediction model. This chapter includes a systematic review and meta-analysis of prognostic factors of adherence to home-based exercise therapy in patients with chronic diseases. Variables are identified, classified and graded. Chapter 5 describes exercise adherence over a 12-month period in patients with COPD following prolonged pulmonary rehabilitation, including clinical implications on health service utilization and possibly more affordable health care. Chapter 6 presents a study on the development of a prediction model for the probability of exercise adherence in patients with COPD already following pulmonary rehabilitation. The study provides an online calculator for practical use of the prediction model. Chapter 7 presents a supplement on the prediction model described in chapter 6. To not only predict adherence, but also to better understand the relationship between determinants and adherence, this supplement was written. It describes the predictors that could potentially had a causal relationship with exercise adherence to complement the prediction model and provides examples of interventions that might be used to possibly enhance exercise adherence. Chapter 8 provides a protocol for a study that will evaluate 1. The safety and effectiveness of self-management within pulmonary rehabilitation (PR) on health outcomes in patients with COPD, 2. the predictive validity of the PATCH tool, and 3. the feasibility and acceptability of self-management and the PATCH tool by patients and physiotherapists. In chapter 9, the general discussion, the results of all chapters are discussed and taken into a broader theoretical and practical perspective. This chapter also includes conclusions and recommendations for further research. References 1. Jakab, M., J. Farrington, S. Borgermans, and F. Mantingh, Health systems respond to noncommunicable diseases: time for ambition. 2018, Denmark: WHO Regional Office for Europe. 2. Zeilstra, A., A. den Ouden, and W. Vermeulen, Middellangetermijn- verkenning zorg 2022-2025 [Medium-term care exploration 2022-2025]. 2019. Available at:
Chapter 1 16 https://www.cpb.nl/sites/default/files/omnidownload/CPBMiddellangetermijnverkenning-zorg-2022-2025-nov2019.pdf (cited November 18 2022). 3. Vermeer, K., Ondersteuning van zelfmanagement: van ‘zorgen voor’ naar ‘zorgen dat’ [Supporting self-management: from "taking care of" to "taking care that]. Nederlands Tijdschrift voor Evidence Based Practice [Dutch Journal of Evidence Based Practice], 2015. 13, 21-23 DOI: 10.1007/s12468-015-0010-9. 4. Huber, M., J.A.Knottnerus, L. Green, H. vd Horst, A.R. Jadad, D. Kromhout, et al., How should we define health? BMJ, 2011. 343, d4163 DOI: 10.1136/bmj.d4163. 5. Holman, H. and K. Lorig, Patient self-management: a key to effectiveness and efficiency in care of chronic disease. Public Health Rep, 2004. 119(3): p. 239-43. 6. Allegrante, J.P., M.T. Wells, and J.C. Peterson, Interventions to support behavioral self-management of chronic diseases. Annu Rev Public Health, 2019. 40, 127-146 DOI: 10.1146/annurev-publhealth-040218-044008. 7. Sabaté, E., Adherence to long-term therapies. Evidence for action 2003, Geneva: World Health Organization. 8. Mold, J., Goal-Directed Health Care: Redefining Health and Health Care in the Era of Value-Based Care. Cureus, 2017. 9, DOI: 10.7759/cureus.1043. 9. Bakker, J.H., Therapietrouw; van ervaren belang naar gedeeld belang [Therapy adherence; from perceived importance to shared importance]. 2016. Available at: https://zoek.officielebekendmakingen.nl/blg-671330.pdf (cited November 18 2022). 10. Meichenbaum, D. and D. Turk, Facilitating treatment adherence. 1987, New York: Plenum. 11. Clark, H., S. Bassett, and R. Siegert, Validation of a comprehensive measure of clinic-based adherence for physiotherapy patients. Physiotherapy, 2018. 104, 136141 DOI: 10.1016/j.physio.2017.07.003. 12. Horne, R., J. Weinman, and N. Barber, Concordance, Adherence and Compliance in Medicine Taking. 2005, London: National Co-ordinating Centre for NHS Service Delivery and Organisation. 13. Richardson, C.R., B. Franklin, M.L. Moy, and E.A. Jackson, Advances in rehabilitation for chronic diseases: improving health outcomes and function. BMJ, 2019. 365: p. l2191. 14. World Health Organization, Global status report on noncommunicable diseases. 2014. Available at: https://apps.who.int/iris/bitstream/handle/10665/148114/9789241564854_eng.pdf (cited November 18 2022). 15. Essery, R., A.W.A. Geraghty, S. Kirby, and L. Yardley, Predictors of adherence to home-based physical therapies: a systematic review. Disabil Rehabil, 2017. 39(6): p. 519-534. 16. Scholz, U., F. Sneihotta, and A. Oeberst, Dynamics in self-regulation: plan execution, self-efficacy and mastery of action plans. Journal of Applied Social Psychology, 2007. 37: p. 2706-2725. 17. Blackstock, F.C., R. ZuWallack, L. Nici, and S.C. Lareau, Why don't our patients with chronic obstructive pulmonary disease listen to us? the enigma of nonadherence. Annals of the American Thoracic Society, 2016. 13(3): p. 317-323. 18. Clay, D.L. and J.A. Hopps, Treatment adherence in rehabilitation: the role of treatment accommodation. Rehabilitation Psychology, 2003. 48(3): p. 215-219.
General introduction 17 19. Myers, L.B. and K. Midence, Adherence to treatment in medical conditions. 1998, London: CRC Press. 20. Chubak, J. and R. Hubbard, Defining and measuring adherence to cancer screening. J Med Screen, 2016. 23(4): p. 179-185. 21. Stone, A.A., S. Shiffman, J.E. Schwartz, J.E. Broderick, and M.R. Hufford, Patient compliance with paper and electronic diaries. Control Clin Trials, 2003. 24(2): p. 182-99. 22. Yuen, H.K., E. Wang, K. Holthaus, L.K. Vogtle, D. Sword, H.L. Breland, and D.L. Kamen, Self-reported versus objectively assessed exercise adherence. Am J Occup Ther, 2013. 67(4): p. 484-9. 23. Yang, C.C. and Y.L. Hsu, A review of accelerometry-based wearable motion detectors for physical activity monitoring. Sensors (Basel), 2010. 10(8): p. 77727788. 24. Babatunde, F.O., J.C. MacDermid, and N. MacIntyre, A therapist-focused knowledge translation intervention for improving patient adherence in musculoskeletal physiotherapy practice. Archives of physiotherapy, 2017. 7(1). 25. Granquist, M., D. Gill, and R. Appaneal, Development of a Measure of Rehabilitation Adherence for Athletic Training. Journal of Sport Rehabilitation, 2010. 19(3): p. 249-267. 26. Ostelo, R., A. Verhagen, and H. de Vet, Onderwijs in wetenschap: Lesbrieven voor paramedici [Teaching science: Teaching letters for paramedics]. 2012, Houten: Bohn Stafleu van Loghum. 27. Stolz, D., T. Mkorombindo, D.M. Schumann, A. Agusti, S.Y. Ash, M. Bafadhel, et al., Towards the elimination of chronic obstructive pulmonary disease: a Lancet Commission. The Lancet, 2022. 400(10356): p. 921-972. 28. Vzinfo.nl. COPD. 2022. Available at: https://www.vzinfo.nl/copd (cited November 18 2022). 29. Voelkel, N.F., Raising Awareness of COPD in Primary Care. Chest, 2000. 117(5, Supplement 2): p. 372S-375S.
Chapter 2 18
Measuring adherence in clinic-based physiotherapy 19 Chapter 2 Measuring adherence in clinic-based physiotherapy; a study of the interrater reliability of a Dutch measurement Ellen Ricke Eric W Bakker Published in International Journal of Physiotherapy and Rehabilitation 2019; 5(1): 1-8
Chapter 2 20 Abstract Introduction: The assessment of adherence forms an important part of positive treatment outcomes, and there is a need to adapting them to the Dutch population. The aim of this study was to evaluate the inter-rater reliability of the Dutch version of the Rehabilitation Adherence Measure for Athletic Training (RAdMAT-NL) in patients who are undertaking physiotherapeutic rehabilitation in a primary physiotherapy practice. Methods: Two groups of patients, 18 with musculoskeletal injuries and 18 with chronic diseases (MS, COPD, dystrophy, Parkinson’s disease and partial paraplegia), participated in this cross-sectional study conducted between November 1 and December 1, 2017. Two matched physiotherapists independently assessed the adherence of a patient at the end of a treatment using the Dutch version of the 16-item RAdMAT. The inter-rater reliability was evaluated using the intraclass correlation coefficient (ICC). The ICC was calculated for all the participants together, after which it was calculated for patients with musculoskeletal injuries and patients with chronic diseases separately. Results: The inter-rater reliability of the RAdMAT-NL is excellent: ICC = 0.98 for all the participants. The inter-rater reliability is also excellent for patients with musculoskeletal injuries (ICC = 0.98) and patients with chronic diseases (ICC = 0.99). Conclusion: The inter-rater reliability of the RAdMAT-NL is excellent in patients who are undertaking physiotherapeutic rehabilitation in a primary physiotherapy practice.
Measuring adherence in clinic-based physiotherapy 21 Introduction Non-adherence to treatment is a problem across therapeutic areas, also including physiotherapy, with non-adherence rates ranging from 25% to 50% [1, 2]. Poor adherence limits the potential of physiotherapeutic rehabilitation to improve patients’ health and quality of life. Furthermore, this non-adherence has been associated with substantial costs (for patients and society), including avoidable morbidity, increased hospital admissions, and prolonged hospital stays [1, 2]. For example, non-adherent patients with type II diabetes can have annual inpatient costs 41% higher compared to adherent patients [3]. Significant costs can be avoided by increasing adherence [3]. So, non-adherence to physiotherapeutic rehabilitation is a problem of increasing concern to all stakeholders in the health system. At the same time, adherence is the most important factor of treatment that can be influenced to achieve positive treatment outcomes [1]. In this study adherence is defined as the extent to which a person’s behavior, taking medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a health care provider [4]. In physiotherapy, adherence is a multi-dimensional concept that could relate to attending appointments, following advice, undertaking prescribed exercises and the performance and frequency of the exercises [5]. Physiotherapists almost always assume that patients are motivated to follow treatment because of their injury/disease. However, literature shows that this assumption might be incorrect [6, 7]. The determinants of adherence in physiotherapy (inactive or moderate active lifestyle at baseline, low adherence to exercise, low self-efficacy, depression, anxiety, helplessness, poor social support, and greater number of perceived barriers to exercise) suggest that adherence is a behavioral problem observed in patients, but with causes beyond the patient [5, 7]. In every situation in which patients have to take responsibility of their own treatment, non-adherence is likely. This is especially true for patients with chronic diseases. Non-adherence increases with the duration and complexity of a treatment, both of which are high for chronic diseases [7]. Poor adherence to longterm therapy severely compromises the effectiveness of treatment. This is a critical health issue, because chronic diseases are increasing in The Netherlands. In the Netherlands (as in western society), the prevalence of chronic diseases is increasing due to the rapid aging of the population and the greater longevity of people with chronic diseases. Also, the prevalence of multi-morbidity (the presence of multiple diseases in the same individual) is rising [8]. Because of the increase of patients with chronic diseases, physiotherapists in the Netherlands have noticed an increase of these patients in their practice. This number will only further increase in the future [9].
Chapter 2 22 Physiotherapists will also benefit from patients adhering more to their treatment. The environment, in which the physiotherapist works, is demanding for evidencebased work with a focus on reduction of healthcare costs. When patients adhere to evidence-based interventions, physiotherapists notice positive results and will not unnecessary change the intervention. This may result in more effective treatments and possibly a shorter treatment period. It will help physiotherapists work effectively, be more cost-efficient and contribute to the patient’s self-management [6, 7]. To increase adherence, it must be measurable. When an unexpected poor outcome is seen in patients, a reliable and valid measurement instrument to assess adherence should be available. That way, the physiotherapist can assess the diverse range of adherence attitudes and behaviors in the patient. The physiotherapist can engage in dialogue with the patient about the non-adherence and can implement strategies to target the attitudes and behaviors of nonadherence. Ultimately this may lead to better treatment outcomes. Because adherence is a multi-dimensional concept, a measurement of adherence also has to be multi-dimensional (measure more domains at the same time) [7, 10]. Currently there is no reference standard for measuring exercise adherence and a lot of measures have been identified in musculoskeletal disorders [11], but only one multi-dimensional instrument has been described to measure adherence in physiotherapy practice: The Rehabilitation Adherence Measure for Athletic Training [12, 13]. The RAdMAT is considered to be reliable, valid, responsive and interpretable at an individual level, easy and simple to use, and low financial cost [14] in patients with musculoskeletal complaints who are visiting a primary physiotherapy practice. Applicability of the RAdMAT in Dutch physiotherapy practices To date, the RAdMAT is available only in English. This original version shows promising psychometric properties. Internal consistency reliabilities range between 0.96 and 0.99 and Cronbach’s a for each level of adherence is acceptable to high [12]. Because a measurement also has to be simple and easy to use [14] a Dutch version of the RAdMAT should be available. For this study a Dutch version of the RAdMAT (RAdMAT-NL) was prepared by a native speaker based on the guidelines of translating questionnaires [15, 16]. This questionnaire, like the original version of the RAdMAT, is a 16-item questionnaire that uses a four-point rating scale (1 = never, 2 = occasionally, 3 = often, 4 = always) [12]. The conceptual meaning of the original measurement was maintained and the setting and the position of the raters were the same as used in the original version of the RAdMAT.
Measuring adherence in clinic-based physiotherapy 23 However, the RAdMAT-NL is a new measurement, so the reliability of the RAdMATNL is unknown. When a measurement is adjusted (translated) or is used for another population (have become a new measurement), it is important to reassess the validity and reliability of the measurement. Reliability is the consistency or repeatability of the measures [14]. There are two aspects of reliability. First the intra-rater reliability: the degree of agreement among repeated administrations of a diagnostic test performed by a single rater. Second is the inter-rater reliability: the degree of agreement among raters [14]. The RAdMAT-NL has to be reliable and valid to ensure that the evaluation is consistent and accurate [14]. If the RAdMAT-NL shows psychometric properties similar to or higher than the original measurement, it may be considered as culturally acceptable [16]. Evaluating the reliability of the RAdMAT-NL would be a first step in the development of a Dutch instrument for measuring adherence in the physiotherapy practice. Therefore, the purpose of this study was to measure the inter-rater reliability of the Dutch version of the RAdMAT (RAdMAT-NL) in patients who are undertaking physiotherapeutic rehabilitation (patients with musculoskeletal complaints and with chronic diseases). Materials and Methods Study design This was a cross sectional study conducted between November 1 and December 1, 2017. Setting A primary physiotherapy practice in the Netherlands was chosen because the original version of the RAdMAT was validated for use in a primary practice setting, and because this practice has a diverse patient population, including patients with musculoskeletal complaints and with chronic diseases, like diabetes, chronic obstructive pulmonary disease (COPD) and multiple sclerosis (MS). The presence of patients with chronic diseases is important, because this study had to evaluate the use of the RAdMAT-NL in this population. Participants Participants were patients undertaking physiotherapeutic rehabilitation in the primary physiotherapy practice who met the inclusion and exclusion criteria. The inclusion criteria were: being at least 18 years old, undertaking rehabilitation at the practice (rather than at home), and having a musculoskeletal injury or a chronic disease. The exclusion criteria were undertaking manual therapy or orofacial
Chapter 2 24 therapy, and insufficient mastery of the Dutch language to complete the questionnaires. Routing The researcher invited patients potentially meeting the inclusion criteria to participate in this study. The researcher provided the patients further information and checked if the patients met the inclusion criteria. Patients who met the criteria and agreed to participate signed an informed consent form and were included in the study, taking into account that half of the patients had musculoskeletal complaints and the other half had chronic diseases. Identifying and including patients continued till the sample size, needed for this study, was reached. In the same period, participating physiotherapists (raters) were invited to participate in this study and were told that the study used informed consent. Baseline variables Participants’ age (year), gender (male/ female), previous history of physiotherapy treatments (yes/no), and physiotherapeutic diagnosis (musculoskeletal injury or chronic disease) were recorded. Study procedure Before measurement, the researcher explained the meaning of adherence and the use of the RAdMAT-NL to the raters. The RAdMAT-NL is a 16-item questionnaire that uses a four-point rating scale and asks about patient clinic-based adherence that includes the patients’ attitudes and communication along with their clinic behaviors [13]. The raters were asked to assess the adherence of the patients independently. First the physiotherapists assessed adherence of three patients as a group. Based on this exercise, consensus was obtained regarding the use of this measurement instrument. Then two physiotherapists were randomly matched (based on there working days) to both assess the adherence of a patient when measurement started. The following characteristics of the physiotherapist were recorded: gender (male/female), completed Master’s degree (yes/no), and professional experience in a primary physiotherapy practice (years). Between November 1 and December 1, 2017, the physiotherapists independently assessed the adherence of a patient at the end of the treatment. Participants were aware that they participated in the study and that they were assessed between November 1 and December 1, but they did not know when the assessment took place. In this way, the participant was blinded for the assessment and could not meet with the rater (preventing information bias). Both physiotherapists independently assessed the patients so, their assessments were not influenced by each other; both raters were blinded for each other’s results. During the study, it
Measuring adherence in clinic-based physiotherapy 25 was assumed that the status of the patient remained unchanged and that the physiotherapists’ method of assessment was standardized [14]. Completed questionnaires were returned to the researcher by the physiotherapists for processing. Sample size The sample size was calculated as follows. In general, reliability coefficients should be at least 0.9 to be interpretable at an individual patient level, while coefficients of at least 0.7 are acceptable at a group level [17]. So, the intended output of the intraclass correlation coefficient (ICC) was 0.9, with 0.7 as the acceptable lower limit. With two raters for one patient, a sample of 18 participants would be enough for a hypothetical ICC of 0.9 with acceptable lower limit of 0.7 (power = 0.80 and α = 0.05) [18]. Since differentiating between musculoskeletal injuries and other diseases was needed, 36 participants were needed. Data analysis Data were analyzed using the Statistical Package for Social Sciences (SPSS) version 20 with an a-level set at 0.05. Data were screened for outliers and tested for normal distribution. Descriptive statistics were used to evaluate the baseline variables of the patients (age, gender, previous history of physiotherapy treatments, and physiotherapeutic diagnosis) and the physiotherapists (gender, completed Master’s degree, and years of professional experience in a primary physiotherapy practice). Variables were expressed in percentages or in the mean ± standard deviation with a range. The inter-rater reliability was evaluated using the intraclass correlation coefficient (2, 1): a two-way random effects single measures model with absolute agreement with a confidence interval of 95%. The ICC was calculated for all the participants, after which it was calculated for patients with musculoskeletal injuries and patients with chronic diseases separately. The ICC describes the compliance between two repeated measures and future repeated measures of adherence [19]. The ICC was interpreted based on the guidelines described by Cicchetti [20]: less than 0.40 = poor; between 0.40 and 0.59 = fair; between 0.60 and 0.74 = good; between 0.751.00 = excellent. Results Thirty-nine people were recruited: 17 males and 22 females. Three were asked to participate in training the physiotherapists to reach consensus about the use of the RAdMAT-NL and 36 participated in the study. Their demographic characteristics are shown in Table 1. Demographic characteristics of the six participating physiotherapists are shown in Table 2. Table 3 shows the mean scores of each rater per patient. The results show a high degree of congruence between the
Chapter 2 26 assessments. This is visually demonstrated in Figure 1, a plot of the measures of the raters. As shown in Table 4, the ICC score for all the participants and for participants with musculoskeletal injuries and chronic diseases were excellent. Table 1 Demographic characteristics patients (n = 36) Variables Gender (male) (%) 47.2 Age (year, mean ± SD, range) 55.5 ± 11.9 (28-73) Previous history of physiotherapy (Treated previously) (%) 33.3 Physiotherapeutic diagnosis (%) - Musculoskeletal injuries - Chronic diseases COPD MS Dystrophy Parkinson Partial paraplegia 50.0 50.0 50.0 27.8 5.6 5.6 11.1 Note: SD: standard deviation; COPD: Chronic Obstructive Pulmonary Disease; MS: Multiple Sclerosis Table 2 Demographic characteristics of the raters (n = 6) Variables Gender (male) (n) 5 Completed Master’s degree (yes) (n) 4 Years of professional experience (year, mean ± SD, range) 14.7 ± 11.3 (1-28) Note: SD: standard deviation
Measuring adherence in clinic-based physiotherapy 27 Table 3 Mean scores of raters Participant Mean rater 1 Mean rater 2 1 31 27 2 39 41 3 39 41 4 39 41 5 42 44 6 43 43 7 45 46 8 45 47 9 52 54 10 53 51 11 57 57 12 57 57 13 58 53 14 58 58 15 58 59 16 59 60 17 60 60 18 60 59 19 33 32 20 36 37 21 40 39 22 40 42 23 41 40 24 43 41 25 43 41 26 44 43 27 54 53 28 54 54 29 54 52 30 54 56 31 56 56 32 57 58 33 58 59 34 58 58 35 59 59 36 60 60
Chapter 2 28 Figure 1 Mean scores per participant according to the two raters Table 4 Inter-rater reliability differentiated by diagnoses and for all participants ICC 95% CI RAdMAT-NLtotal 0.98 0.97-0.99 RAdMAT-NLmusculoskeletal 0.98 0.94-0.99 RAdMAT-NLchronic 0.99 0.98-0.99 Note: ICC: Intraclass correlation coefficient; CI: Confidence Interval; RAdMAT-NL: Rehabilitation Adherence Measure for Athletic Training the Dutch version Discussion The aim of this study was to measure the inter-rater reliability of the Dutch version of the RAdMAT (RAdMAT-NL) in patients (with musculoskeletal injuries and with chronic diseases) who were undertaking physiotherapeutic rehabilitation in a primary physiotherapy practice. The results show that the inter-rater reliability of the RAdMAT-NL is excellent; ICC = 0.98 for all participants. The inter-rater reliability is also excellent in patients with musculoskeletal injuries (the original population) (ICC = 0.98) and patients with chronic diseases, like MS, COPD, dystrophy, Parkinson’s
Measuring adherence in clinic-based physiotherapy 29 disease and partial paraplegia (ICC = 0.99). This is important for both clinical practice and further research, because a strong inter-rater reliability is necessary for interpreting change in the individual patient [19]. The results of this study are in accordance with the results of previous research [12, 13], which showed that the original version of the RAdMAT can reliably measure adherence in the physiotherapy practice in patients with musculoskeletal injuries and has an excellent inter-rater reliability (range ICC = 0.96-0.99). This study shows that the RAdMAT-NL also has an excellent inter-rater reliability. This study adds to previous research by showing that the RAdMAT-NL is also applicable in patients with chronic diseases. As such, the RAdMAT-NL meets almost all requirements of an appropriate measurement instrument: it is reliable, interpretable at an individual level, easy and simple to use, and low financial cost [14]. Because the measurement instrument is in Dutch, it is easy for Dutch people to complete and to analyze. Strengths and limitations The use of a diverse population was strength of this study, but the study also has weaknesses. First, the results of this study were obtained in one physiotherapy practice where the raters knew most of the participants. Although participants were blinded for the assessment, one of the raters might have recently worked with one or more of the participants. This would give the rater more information about the participant than the other rater, which would lead to information bias. If information bias occurred, then the inter-rater reliability could be underestimated. However, the inter-rater reliability was excellent, so probably information-bias did not occur. Second, raters had to assess participants independently, but whether this happened at all times could not be ensured. If mutual consultation occurred, then the inter-rater reliability could be overestimated. Nevertheless, the results are promising as the first step of the development of a Dutch instrument for measuring adherence in the physiotherapy practice. When an unexpected poor outcome is seen in patients, it is recommended to complete the RAdMAT-NL for this patient. That way, the physiotherapist can assess whether there is non-adherence in the patient and thus whether the intervention should be changed. Also, the physiotherapist can engage in dialogue with the patient about the non-adherence. Ultimately this may lead to better treatment outcomes [7, 10, 13]. To provide tailored interventions for each patient, reliable measurement instruments are needed. Using reliable measurement instruments has added value for patients, physiotherapists and society. Using reliable measurements can increase adherence in patients and adherence can in turn be a tool to achieve health gains in patients [7]. Better treatment results contribute to better quality of life and lower healthcare costs for patients and society [3, 7].
Chapter 2 30 To achieve this, more research to the RAdMAT-NL is needed. Future studies should increase the reliability by using more raters from multiple primary physiotherapy practices. This will provide a more definitive conclusion regarding the inter-rater reliability of the RAdMAT-NL for patients with musculoskeletal injuries and with chronic diseases. Also, future research should perform a factor analysis to demonstrate the multidimensional character, the three subscales, of the RAdMAT-NL (attendance/participation, communication, and attitude/effort) [13]. Demonstrating these subscales would show the multidimensional character of the RAdMAT-NL and that it can be used to increase adherence through interventions for specific attitudes and behaviors. Conclusion In conclusion, the inter-rater reliability of the RAdMAT-NL is excellent in patients who are undertaking physiotherapeutic rehabilitation in a primary physiotherapy practice. References 1. Bassett, S. Measuring Patient Adherence to Physiotherapy. Journal of Novel Physiotherapies, 2012. 2, DOI: 10.4172/2165-7025.1000e124. 2. Campbell, R., M. Evans, M. Tucker, B. Quilty, P. Dieppe, and J.L. Donovan, Why don’t patients do their exercises? Understandig non-compliance with physiotherapy in patients with osteoarthritis of the knee. Journal of Epidemiology and Community Health, 2001. 55(2): p. 132-138. 3. McGuire, M. and A. Iuga, Adherence and health care costs Risk Management and Healthcare Policy, 2014. 7: p. 35-44. 4. Meichenbaum, D. and D. Turk, Facilitating treatment adherence. 1987, New York: Plenum. 5. Jack, K., S.M. McLean, J.K. Moffett, and E. Gardiner, Barriers to treatment adherence in physiotherapy outpatient clinics: A systematic review. Manual Therapy, 2010. 15, 220-228 DOI: 10.1016/j.math.2009.12.004. 6. Al-Eisa, E., Indicators of adherence to physiotherapy attendance among Saudi female patients with mechanical low back pain: a clinical audit. BMC Musckuloskeletal Disorders, 2010. 11(1). 7. Sabaté, E., Adherence to long-term therapies. Evidence for action 2003, Geneva: World Health Organization. 8. van Oostrom, S., R. Gijsen, I. Stirbu, J.C. Korevaar, F.G. Schellevis, H.S. Picavet, and N. Hoeymans, Time trends in prevalence of chronic diseases and multimorbidity not only due to aging: data from general practices and health surveys. PLoS One, 2016. 11(8): p. e0160264.
Measuring adherence in clinic-based physiotherapy 31 9. Kooijman, M.K, I.C.S. Swinkels, J.A. Barten, and C. Veenhof, Fysiotherapeutisch zorggebruik door patiënten met een chronische aandoening [Physiotherapy care utilization by patients with chronic conditions]. 2011, Nivel: Utrecht. 10. Miller, N.H. Adherence behavior in the prevention and treatment of cardiovascular disease. J Cardiopulm Rehabil Prev, 2012. 32, 63-70 DOI: 10.1097/HCR.0b013e318235c729. 11. Babatunde, F.O., J.C. MacDermid, and N. MacIntyre, A therapist-focused knowledge translation intervention for improving patient adherence in musculoskeletal physiotherapy practice. Archives of physiotherapy, 2017. 7(1). 12. Granquist, M., D. Gill, and R. Appaneal, Development of a Measure of Rehabilitation Adherence for Athletic Training. Journal of Sport Rehabilitation, 2010. 19(3): p. 249-267. 13. Clark, H., S. Bassett, and R. Siegert Validation of a comprehensive measure of clinic-based adherence for physiotherapy patients. Physiotherapy, 2018. 104, 136141 DOI: 10.1016/j.physio.2017.07.003. 14. Ostelo, R., A. Verhagen, and H. de Vet, Onderwijs in wetenschap: Lesbrieven voor paramedici [Teaching science: Teaching letters for paramedics]. 2012, Houten: Bohn Stafleu van Loghum. 15. Beaton, D., C. Bombardier, F. Guillemin, and M.B. Ferraz, Guidelines for the process of cross-cultural adaptation of self-report measures. Spine 2000. 25(24): p. 3186-3191. 16. Nusbaum, L., J. Natour, M.B. Ferraz, and J. Goldenberg, Translation, adaptation and validation of the Roland-Morris questionnaire: Brazil Roland-Morris. Brazilian Journal of Medical and Biological Research, 2001. 34(2): p. 203-210. 17. Streiner, D.L., G.R. Norman, and J. Cairney, Health measurement scales; a practical guide to their development and use. 2015, United Kingdom: Oxford University Press. 18. Walter, S., M. Eliasziw, and A. Donner, Sample size and optimal designs for reliability studies. Statistics in Medicine, 1998(2): p. 420-428. 19. Shrout, P. and J. Fleiss, Intraclass correlations: uses in assessing rater reliability. Psychological Bulletin, 1979. 86(2): p. 420-428. 20. Cicchetti, D., Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment, 1994. 6(4): p. 284-290.
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Measuring adherence in clinic-based physiotherapy 33 Chapter 3 Measuring adherence to pulmonary rehabilitation: a prospective validation study of the Dutch version of the Rehabilitation Adherence Measure for Athletic Training (RAdMAT-NL) Ellen Ricke Robert Lindeboom Arie Dijkstra Eric W Bakker Under review at Patient Preference and Adherence 2023 Digital Object Identifier 10.21203/rs.3.rs-2088726/v1
Chapter 3 34 Abstract Introduction: When measuring exercise adherence in patients with chronic obstructive pulmonary disease (COPD), instruments covering all relevant aspects related to adherence should be used. The Rehabilitation Adherence Measure for Athletic Training (RAdMAT) seems a promising instrument. A Dutch version of this instrument (RAdMAT-NL) is available. The aim of this study was 1. to explore the dimensionality and construct validity of the RAdMAT-NL in patients with chronic obstructive pulmonary disease (COPD) and 2. to examine if the RAdMAT-NL could be used as a single measure of adherence. Methods: In this prospective study participated 193 patients with COPD, who were undertaking pulmonary rehabilitation (PR) in 53 primary physiotherapy practices in The Netherlands and Belgium. At one month, two and three months after inclusion, patients and their physiotherapist provided measures about the rehabilitation including the RAdMAT-NL. Principal Axis Factoring (PAF) was performed to explore the dimensionality of the RAdMAT-NL. Rasch analysis was used for testing unidimensionality of the RAdMAT-NL. Spearman’s correlations were calculated with other indicators of adherence, including SIRAS score, percentage attendance and change in exercise skills, to determine construct validity. Results: PAF demonstrated two dimensions of the RAdMAT-NL, Participation and Communication, explaining 50.8% of the total variance. Rasch analysis showed that without the communication items (Andersen LR-test, p-value < 0.001) the RAdMAT-NL can be used as a single score for adherence. Medium to large significant positive correlations between the RAdMAT-NL subscale Participation and different measures of adherence supported its validity. Conclusion: The RAdMAT-NL can be used as an interim assessment measure of exercise adherence for patients who are not progressing as expected. The 13 items of the Participation dimension can be used as a single score for adherence.
Measuring adherence to pulmonary rehabilitation 35 Introduction From a rehabilitation context, adherence has been defined as an ‘active, voluntary collaborative involvement of the patient in a mutually acceptable course of behavior to produce a desired preventative or therapeutic result’ [1]. The behaviors that constitute exercise adherence may vary, and largely depends on the type of injury or condition of presenting patients. These behaviors may include attendance at clinic appointments, the extent to which patients follow the prescribed treatment, and the communication with their healthcare provider about their recovery in order to receive feedback about their home-based rehabilitation activities [2]. Rehabilitation more and more involves self-management, and requires effort from patients themselves in following prescribed exercises at home. This makes adherence increasingly important [3]. Adherence is important in many aspects of healthcare as it is related to clinical outcomes, and to the (economic) burden for healthcare providers [4]. Patients who fail to adhere to the prescribed exercises, may experience prolonged duration of treatment and less favorable treatment results [5]. Also, the increase in chronic diseases makes adherence important for all stakeholders in the healthcare system [3]. To keep healthcare affordable and improving patient outcomes, attention must be paid to adherence [6]. One chronic disease where adherence is of particular importance is chronic obstructive pulmonary disease (COPD). Fewer than half of treatments for COPD are taken as prescribed [7]. The management of a disease like COPD is difficult because prescribed exercises largely take place at home, with patients and their caregivers making decisions as to whether exercises should be started or continued, often without consulting their healthcare provider [8]. As a result, it is often not clear to professionals whether patients are adherent or not. Professionals tend to make their own judgements about the extent of the suspected nonadherence in patients by asking or by observing treatment progress [9]. These judgements may be incorrect; their validity is uncertain. Therefore, a standardized instrument is needed to quantify the extent and reasons for non-adherence [9] as early as possible. On the basis of early signals, the treatment might be adapted to the specific needs of an individual patient or measures can be taken to improve adherence [10]. Literature shows that some instruments are available to measure adherence to exercise interventions [11]. Of the instruments mentioned, only two appear to be valid and reliable: the Sport Injury Rehabilitation Adherence Scale (SIRAS) [12] and the Rehabilitation Adherence Measure for Athletic Training (RAdMAT) [13]. However, in the context of measuring adherence, an additional requirement for the instrument is that it must be multidimensional, as adherence is a multidimensional
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