UMC Utrecht Brain Center To exercise or not to exercise: Exploring Adherence to Home-Based Exercise in patients with Low Back Pain Remco Arensman
To exercise or not to exercise: Exploring Adherence to Home-Based Exercise in patients with Low Back Pain Remco Arensman
To exercise or not to exercise: Exploring Adherence to Home-Based Exercise in patients with Low Back Pain. Utrecht University, Utrecht, The Netherlands © Copyright: Remco Arensman, 2024, Harmelen, The Netherlands ISBN: 978-94-6506-432-1 DOI: https://doi.org/10.33540/2478 Provided by thesis specialist Ridderprint, ridderprint.nl Printing: Ridderprint Cover illustration: Remco Arensman Layout and design: Bart Roelofs, persoonlijkproefschrift.nl The research presented in this thesis was conducted at the Center for Physical Therapy Research and Innovation in Primary Care (AWF), a structural collaboration between the Julius Health Care Centers (Utrecht, The Netherlands), the Department of Rehabilitation, Physiotherapy Science & Sport (UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, The Netherlands), the Research Group Innovation of Human Movement Care (Expertise Center Healthy Urban Living, HU University of Applied Sciences, Utrecht, The Netherlands), and the Research Group Empowering Healthy Behaviour (Department of Health Innovations and Technology, Fontys University of Applied Sciences, Eindhoven, The Netherlands).
“Science isn’t about why, it’s about why not!” — J.K. Simmons (Portal 2) —
TABLE OF CONTENTS Chapter 1 General introduction 8 Chapter 2 Measuring exercise adherence in patients with low back pain: development, validity, and reliability of the EXercise Adherence Scale (EXAS) 22 Chapter 3 Patient perspectives on using a smartphone application to support home-based exercise during physical therapy treatment: a qualitative study 44 Chapter 4 Effectiveness and cost-effectiveness of stratified blended physiotherapy in patients with non- specific low back pain: study protocol of a cluster randomized controlled trial 64 Chapter 5 The 3-Month Effectiveness of a Stratified Blended Physiotherapy Intervention in Patients With Nonspecific Low Back Pain: Cluster Randomized Controlled Trial 92 Chapter 6 Trajectories of Adherence to Home-Based Exercise Recommendations Among People With Low Back Pain: A Longitudinal Analysis 124 Chapter 7 Exploring the association between adherence to home-based exercise recommendations and recovery of nonspecific low back pain: a prospective cohort study. 146 Chapter 8 General discussion 164 Chapter 9 General summary 180 Chapter 10 Samenvatting 186 Appendices About the author List of publications Author’s contributions PhD portfolio Dankwoord 194 195 197 199 201
Chapter 1
General introduction
10 Chapter 1 INTRODUCTION Physiotherapy is pivotal in managing musculoskeletal (MSK) conditions (1). Central to the management of MSK conditions is the biopsychosocial model, which highlights the complex relations between biological, psychological, and social factors in shaping the health and well-being of individuals with MSK pain (2). To translate the biopsychosocial model to clinical practice, clinical guidelines provide best practice recommendations for the assessment and treatment of MSK conditions, emphasizing the importance of patient education, self-management support, and interventions focused on physical activity and exercise (3). This evidence-based approach promotes active lifestyles and physical activity, offering short and long-term pain relief. It integrates components like manual therapy, patient education, and exercise therapy, typically provided by physiotherapists (3,4). Exercise therapy in MSK conditions Exercise therapy is “the systematic performance or execution of planned physical movements or activities intended to enable the patient or client to remediate or prevent impairments of body functions and structures, enhance activities and participation, reduce risk, optimize overall health, and enhance fitness and well-being“ (5). Exercise therapy is effective in managing musculoskeletal pain, demonstrating medium to large pain reduction effects and functional improvements compared to no exercise or other control (6). However, the effects vary between different MSK conditions, and optimal content and mode of delivery of exercise therapy remains inconclusive (7). Exercise therapy can be recommended as either supervised exercise by a physiotherapist, home-based exercise (HBE), or a combination of both. In supervised exercise, patients perform exercises at the physiotherapist’s clinic, where the therapist provides instruction, guidance, and coaching. To maintain endurance performance, healthy adults should have at least two exercise sessions per week, while maintaining strength requires one session, or two for older individuals (8). For enhanced endurance and strength, an additional exercise session is necessary to achieve the minimum effective dose (9,10). However, supervised exercises three or more times a week can be costly and time-consuming. To address these challenges, HBE supplements in-clinic sessions, allowing patients to continue exercising at home (11). This not only increases treatment dose, but also reduces the financial burden on the healthcare system by decreasing the need for supervised sessions over the course of treatment and it affords patients the flexibility to exercise according to their own schedules. Given these advantages, it is no surprise that many studies investigated the effectiveness of HBE interventions on reducing pain and disability in musculoskeletal conditions (12–17).
11 General introduction Exercise for low back pain The most prevalent musculoskeletal condition is low back pain (LBP) and it affects a substantial proportion of the adult population worldwide (18). LBP leads to significant disability, economic burden, and reduced quality of life (19,20). A key treatment for LBP is exercise therapy, including supervised exercises and HBE, provided by physiotherapists to boost physical function, alleviate pain, facilitate recovery, and enhance selfmanagement (21). HBE consists of targeted exercises prescribed by physiotherapists for home completion to enhance body functions such as joint mobility, muscle strength, or stability (22). Given the benefit of HBE in LBP management and its research interest, it’s surprising that a recent review shows that only 32% of supervised exercise trials for LBP included some form of HBE (23). Moreover, just 45% of these HBE trials reported on patient adherence to the exercise recommendations (23). While there is no existing research specifically examining the consequences of non-adherence to HBE, it is anticipated that these effects might mirror those of non-adherence to medication, potentially leading to substantial economic strain on the healthcare system (24). Regardless of the economic implications, the effectiveness of an exercise intervention is intrinsically linked to the patient’s adherence to the recommended exercise regimen. Adherence to HBE recommendations and its measurement Adherence is usually conceptualized as a behavior and 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” by the World Health Organization (25). Applied to patient adherence to HBE recommendations, adherence would be defined as “the extent to which a person’s behavior corresponds with agreed HBE recommendations from a health care provider”. In this context, the HBE recommendations include frequency (i.e. number of exercise sessions per day or week); intensity (i.e. number of repetitions per exercise session); and quality of performance of the HBE program (how well did the patient perform the exercises compared to the instructions). Despite a clear definition, measuring adherence to HBE recommendations remains a challenge. Various methods for measuring HBE adherence are described in the literature, including diaries, questionnaires, logs, visual scales, tally counters, and single-item questions (23,26–28). However, standardized, valid, and reliable tools to measure adherence are lacking, leading to difficulties in quantifying adherence and understanding its role in treatment outcomes. For instance, to accurately gauge the effectiveness of interventions that include HBE, it is essential to have a reliable method for assessing patients’ adherence to these exercises. Consequently, the development of such a measurement tool is crucial for accurately evaluating the effectiveness of HBEbased interventions, investigating the relationship between adherence to HBE and clinical outcomes , and improving strategies for enhancing adherence in patients with LBP. 1
12 Chapter 1 Strategies to improve adherence Strategies to improve patients’ adherence include physiotherapist support, limiting the exercise regimen to two to four key exercises, enhancing patient self-motivation and self-efficacy (29), improving physiotherapist communication skills (30), and using behavioral change techniques (31). However, while evidence on these strategies’ shortterm effectiveness is mixed, they appear ineffective for long-term adherence (32). Digital health technologies, designed to aid clinicians and patients, offer a potential solution (33,34). The use of digital health technologies such as apps or web-based platforms during treatment has shown promising results. For example, studies found that online apps with personalized exercises, video guides, and exercise reminders enhance HBE adherence, exercise quality, and therapist-patient interactions (35,36). For example, an app developed to provide patients with the HBE recommendations from their physiotherapist on their smartphone combined with remote support resulted in higher adherence compared to paper handouts alone (35). Smartphone apps can aid in patient self-management and adherence to HBE by incorporating persuasive design elements (33,36–38). Persuasive design seeks to motivate users towards a desired behavior, either short-term or continuously (39). Persuasively designed apps use personalized feedback based on performance, reward systems, and reminders to engage patients actively (33,40). Incorporating self-management tips from credible sources like physiotherapists, other patients, or public figures can further motivate patients to follow the app’s guidance (33,41). Another advantage of the app lies in its constant availability, unlike the limited number and duration of face-to-face sessions with a physiotherapist. In a study investigating an app to support treatment of patients with osteoarthritis combined with face-to-face physiotherapy, patients indicated it improved treatment adherence and continuity between physiotherapist sessions (42,43). Despite the apparent advantages of the integration of the app in usual care, the acceptability, satisfaction, and performance of such technologies from the patient’s perspective are not well-understood and require further investigation. Development of e-Exercise LBP The e-Exercise LBP intervention was designed to enhance both the effectiveness and patient adherence to physiotherapy for patients with LBP. The intervention was developed through a multiphase, iterative process based on the Center for eHealth Research (CeHRes) Roadmap principles (44). This intervention adapts the existing e-Exercise program for patients with hip/knee osteoarthritis (e-Exercise OA), improving physical function, pain, tiredness, quality of life, and self-efficacy (42,45,46). Patients’ positive responses and high engagement with e-Exercise OA’s online component, coupled with physiotherapists’ feedback, shaped the e-Exercise LBP’s development (43,47). Additionally, persuasive design elements (personalization, motivation,
13 General introduction triggers, and conditioning) were implemented in the design of the e-Exercise app to facilitate and support behavior change in patients, and increase adherence to exercise recommendations from the physiotherapist. In total, fourteen different behavioral change techniques (such as goal setting, self-monitoring, shaping knowledge, tailored feedback, and shaping knowledge) were included in the app. The first three steps of the CeHRes Roadmap, namely contextual inquiry, value specification, and design, were followed in the development of e-Exercise LBP (44). Subsequently, a multicenter feasibility study tested the prototype, confirming its potential in reducing disability and pain (48). Based on these results and end-user usability experiences, the e-Exercise LBP prototype was further refined in preparation for broader operationalization and evaluation. e-Exercise LBP The e-Exercise LBP intervention uses a stratified blended approach, merging an app with traditional face-to-face physiotherapy to enhance treatment adherence and effectiveness. Both the app and in-person treatments adhere to the LBP guidelines set by the Royal Dutch Society for Physiotherapy (49). To improve the effectiveness and efficiency of physiotherapy care, treatment is stratified based on the patient’s risk of developing persistent LBP using the Keele STarT Back Screening Tool (50,51). The intervention’s duration, session count, and content are customized for three risk groups from the tool: low, medium, and high (52). The app features an information module with 12 weekly self-management themes, including assignments related to the etiology of LBP, physical activity, patient experiences, pain management, and psychosocial factors related to LBP. The app also includes an exercise module with a HBE program tailored to the patient’s prognostic risk profile, and a physical activity module containing a goal-oriented training program intended to help the patient maintain or improve their level of physical activity. App support duration varies by risk group for persistent complaints: three weeks for low risk, and twelve for medium and high risk (50). Patients can access the app content even after this period. The app’s content varies based on the patient’s risk level, with the physical activity module and graded activity functionality added for “medium” and “high risk” patients. The physiotherapist can monitor the patient’s use of the app, discuss assignments with the patient, and modify the HBE recommendations when needed. This enables personalized care adjustments to maintain patient adherence and optimize intervention results. Post-program, the app sends reminders every other week for six months to encourage ongoing adherence to a physically active lifestyle as recommended by the physiotherapist. Trajectories of adherence to HBE recommendations While the e-Exercise LBP program supports adherence, individual variations are likely due to numerous factors related to both patients and therapists (29,53–57). Additionally, 1
14 Chapter 1 adherence is also likely to vary over time during the treatment period among patients with LBP, resulting in distinct trajectories of adherence. While studies have yet to explore common adherence trajectories for patients with LBP, other patient groups have shown such patterns (58). Different trajectories imply varied clinical needs, and identifying a patient’s trajectory early can help clinicians tailor support and coaching to enhance adherence. Therefore, investigating the unique trajectories of adherence to HBE recommendations in patients with LBP has the potential to increase the effectiveness of interventions for this patient group. Adherence and outcomes Although it’s often thought that adhering to HBE directly impacts clinical outcomes, the link between adherence and LBP recovery may be more intricate, meriting deeper exploration. Only in more recent years have higher quality measurement instruments been published, allowing for more detailed and longitudinal measurement of adherence to HBE recommendations (22,59). Accordingly, this thesis concludes by examining how adherence to HBE influences LBP recovery in patients receiving physiotherapy. In summary, this thesis describes a comprehensive exploration of adherence to HBE programs during the treatment of LBP. A key focus is developing a new tool to measure HBE adherence, enabling the assessment of adherence and its impact on therapeutic results. The research examines patient views on digital tools supporting HBE in physiotherapy and evaluates the clinical effectiveness, cost-effectiveness, and impact on adherence rates of the e-Exercise LBP intervention for patients with LBP. Finally, the thesis aims to identify distinct trajectories of adherence to HBE recommendations and examine the associations between adherence and recovery from LBP. Through these analyses, the thesis aims to offer new insights to healthcare professionals, potentially enhancing LBP management with a deeper understanding of adherence to HBE and its links to recovery. The thesis focusses on adherence to HBE recommendations and is part of the e-Exercise LBP trial. For a more comprehensive evaluation of the (cost-)effectiveness of the e-Exercise LBP trial, interested readers are referred to the thesis “e-Exercise Low Back Pain: Stratified blended physiotherapy for patients with nonspecific low back pain” (60). Outline of the thesis Chapter 2 delves into the development and validation of the Exercise Adherence Scale (EXAS), an instrument specifically designed to measure adherence to HBE programs recommended by physiotherapists. This chapter provides a foundation for the subsequent investigations by establishing a reliable tool for quantifying adherence. Chapter 3 presents a qualitative study to understand patient perspectives on the acceptability, satisfaction, and performance of an app designed to support home-based
15 General introduction exercise. This study provides insights into the app’s benefits from the users’ perspective and how it impacts their adherence to exercise recommendations. Chapter 4 describes the protocol for a cluster randomized controlled trial, investigating the effectiveness and cost-effectiveness of stratified blended physiotherapy in patients with LBP. The intervention combines face-to-face physiotherapy with an app to improve self-management skills and adherence to exercise recommendations. Chapter 5 presents the results of a cluster randomized controlled trial investigating the 3-month effectiveness and cost-effectiveness of e-Exercise LBP (a stratified blended physiotherapy intervention) compared to usual care physiotherapy in patients with LBP. In Chapter 6, the study uses a longitudinal analysis to identify distinct trajectories of adherence to HBE recommendations among people with LBP. Additionally, the study aims to identify whether baseline characteristics can predict trajectories of adherence to inform better patient management. Chapter 7 explores the association between adherence to HBE recommendations and recovery from LBP. This study examines whether high adherence rates improve clinical outcomes in patients LBP. Lastly, Chapter 8 presents the discussion on the findings and methodological considerations of chapters 2 through 7. Furthermore, the implications for clinical practice, society, education, and future research are described. The thesis ends with a summary in English and in Dutch. 1
16 Chapter 1 REFERENCES 1. Fullen BM, Wittink H, De Groef A, Hoegh M, McVeigh JG, Martin D, et al. Musculoskeletal Pain: Current and Future Directions of Physical Therapy Practice. Arch Rehabil Res Clin Transl. 2023;5:100258. 2. Engel GL. The Need for a New Medical Model: A Challenge for Biomedicine. Science (1979). 1977;196(4286):129–36. 3. Lin I, Wiles L, Waller R, Goucke R, Nagree Y, Gibberd M, et al. What does best practice care for musculoskeletal pain look like? Eleven consistent recommendations from high-quality clinical practice guidelines: Systematic review. Br J Sports Med. 2020;54(2):79–86. 4. Guillon M, Rochaix L, Dupont JCK. Cost-effectiveness of interventions based on physical activity in the treatment of chronic conditions: A systematic literature review. Int J Technol Assess Health Care. 2018;34(5):481–97. 5. American Physical Therapy Association. APTA Guide to Physical Therapist Practice 4.0. 2023. https://guide.apta.org. Accessed 7 Nov 2023. 6. Babatunde OO, Jordan JL, Van der Windt DA, Hill JC, Foster NE, Protheroe J. Effective treatment options for musculoskeletal pain in primary care: A systematic overview of current evidence. PLoS One. 2017;12(6):e0178621-. 7. van Seben R, van der Valk I, Huis in ’t Veld T, Rodenburg G. Substitutie van zorg: Fyio- en oefentherapie op de juiste plek. Rotterdam; 2020 Dec. 8. Spiering BA, Mujika I, Sharp MA, Foulis SA. Maintaining Physical Performance: The Minimal Dose of Exercise Needed to Preserve Endurance and Strength Over Time. J Strength Cond Res. 2021;35(5):1449–58. 9. Borde R, Hortobágyi T, Granacher U. Dose–Response Relationships of Resistance Training in Healthy Old Adults: A Systematic Review and Meta-Analysis. Sports Medicine. 2015;45(12):1693–720. 10. Androulakis-Korakakis P, Fisher JP, Steele J. The Minimum Effective Training Dose Required to Increase 1RM Strength in Resistance-Trained Men: A Systematic Review and MetaAnalysis. Sports Medicine. 2020;50(4):751–65. 11. Hayden JA, Van Tulder MW, Tomlinson G. Systematic Review: Strategies for Using Exercise Therapy To Improve Outcomes in Chronic Low Back Pain. Ann Intern Med. 2005;142(9):776– 85. 12. Jakobsen MD, Sundstrup E, Brandt M, Jay K, Aagaard P, Andersen LL. Effect of workplaceversus home-based physical exercise on musculoskeletal pain among healthcare workers: A cluster randomized controlled trial. Scand J Work Environ Health. 2015;41(2):153–63. 13. Daly RM, Gianoudis J, Hall T, Mundell NL, Maddison R. Feasibility, usability, and enjoyment of a home-based exercise program delivered via an exercise app for musculoskeletal health in community-dwelling older adults: Short-term prospective pilot study. JMIR mhealth uhealth. 2021;9(1):e21094. 14. Rören A, Yagappa DM, Théry C, Lefèvre-Colau MM, Rannou F, Nguyen C. Remote telerehabilitation to maintain adherence to home-based exercise therapy in people with musculoskeletal disorders: A pilot study. Ann Phys Rehabil Med. 2023;66(5):101723.
17 General introduction 15. Macías-Hernández SI, Morones-Alba JD, Tapia-Ferrusco I, Vélez-Gutiérrez OB, HernándezDiaz C, Nava-Bringas TI, et al. A home-based exercise program for temporomandibular joint osteoarthritis: Pain, functionality, and joint structure. J Korean Assoc Oral Maxillofac Surg. 2022;48(1):50–8. 16. Kuijlaars IAR, Sweerts L, Nijhuis-van der Sanden MWG, van Balen R, Staal JB, van Meeteren NLU, et al. Effectiveness of Supervised Home-Based Exercise Therapy Compared to a Control Intervention on Functions, Activities, and Participation in Older Patients After Hip Fracture: A Systematic Review and Meta-analysis. Arch Phys Med Rehabil. 2019;100:101–14. 17. Quentin C, Bagheri R, Ugbolue UC, Coudeyre E, Pélissier C, Descatha A, et al. Effect of home exercise training in patients with nonspecific low-back pain: A systematic review and meta-analysis. Int J Environ Res Public Health. 2021;18(16):8430. 18. James SL, Abate D, Abate KH, Abay SM, Abbafati C, Abbasi N, et al. Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: a systematic analysis for the Global Burden of Disease Study 2017. Lancet. 2018;392(10159):1789–858. 19. Singh K, Andersson G, Watkins-Castillo SI. Low Back and Neck Pain. In: United States Bone and Joint Initiative: The Burden of Musculoskeletal Diseases in the United States (BMUS). Fourth Edition. Rosemont, IL: United States Bone and Joint Initiative. 20. Buchbinder R, van Tulder M, Öberg B, Costa LM, Woolf A, Schoene M, et al. Low back pain: a call for action. Lancet. 2018;391(10137):2384–8. 21. Foster NE, Anema JR, Cherkin D, Chou R, Cohen SP, Gross DP, et al. Prevention and treatment of low back pain: evidence, challenges, and promising directions. Lancet. 2018;391(10137):2368–83. 22. Arensman RM, Geelen RH, Koppenaal T, Veenhof C, Pisters MF. Measuring exercise adherence in patients with low back pain: development, validity, and reliability of the EXercise Adherence Scale (EXAS). Physiother Theory Pract. 2022;38(7):928–37. 23. Lee GT, Himler P, Rhon DI, Young JL. Home Exercise Programs Are Infrequently Prescribed in Trials of Supervised Exercise for Individuals With Low Back Pain: A Scoping Review of 292 Randomized Controlled Trials. JOSPT. 2023;53(3):120–42. 24. Cutler RL, Fernandez-Llimos F, Frommer M, Benrimoj C, Garcia-Cardenas V. Economic impact of medication non-adherence by disease groups: A systematic review. BMJ Open. 2018;8(1). 25. Sabaté E. Adherence to long-term therapies: Evidence for action. Sabaté E, editor. European Journal of Cardiovascular Nursing. Geneva; 2003. 26. Bollen JC, Dean SG, Siegert RJ, Howe TE, Goodwin VA. A systematic review of measures of self-reported adherence to unsupervised home-based rehabilitation exercise programmes, and their psychometric properties. BMJ Open. 2014;4(6):e005044. 27. Frost R, Levati S, McClurg D, Brady M, Williams B. What Adherence Measures Should Be Used in Trials of Home-Based Rehabilitation Interventions? A Systematic Review of the Validity, Reliability, and Acceptability of Measures. Arch Phys Med Rehabil. 2017;98(6):12411256.e45. 28. McLean S, Holden MA, Potia T, Gee M, Mallett R, Bhanbhro S, et al. Quality and acceptability of measures of exercise adherence in musculoskeletal settings: A systematic review. Rheumatology. 2017;56(3):426–38. 1
18 Chapter 1 29. Bachmann C, Oesch P, Bachmann S. Recommendations for Improving Adherence to HomeBased Exercise: A Systematic Review. Phys Medizin Rehabilitationsmedizin Kurortmedizin. 2018;28:20–31. 30. Lonsdale C, Hall AM, Murray A, Williams GC, McDonough SM, Ntoumanis N, et al. Communication Skills Training for Practitioners to Increase Patient Adherence to HomeBased Rehabilitation for Chronic Low Back Pain: Results of a Cluster Randomized Controlled Trial. Arch Phys Med Rehabil. 2017;98(9):1732-1743.e7. 31. Eisele A, Schagg D, Krämer LV, Bengel J, Göhner W. Behaviour change techniques applied in interventions to enhance physical activity adherence in patients with chronic musculoskeletal conditions: A systematic review and meta-analysis. Patient Educ Couns. 2019;102(1):25-36. 32. McLean SM, Burton M, Bradley L, Littlewood C. Interventions for enhancing adherence with physiotherapy: A systematic review. Man Ther. 2010;15(6):514–21. 33. Kelders SM, Kok RN, Ossebaard HC, Van Gemert-Pijnen JE. Persuasive System Design Does Matter: a Systematic Review of Adherence to Web-based Interventions. J Med Internet Res. 2012;14(6):e152. 34. Wentzel J, Van der Vaart R, Bohlmeijer ET, Van Gemert-Pijnen JEWC. Mixing online and face-to-face therapy: How to benefit from blended care in mental health care. JMIR Ment Health. 2016;3(1):e9. 35. Lambert TE, Harvey L a., Avdalis C, Chen LW, Jeyalingam S, Pratt C a., et al. An app with remote support achieves better adherence to home exercise programs than paper handouts in people with musculoskeletal conditions: A randomised trial. J Physiother. 2017;63(3):161–7. 36. Bennell KL, Marshall CJ, Dobson F, Kasza J, Lonsdale C, Hinman RS. Does a Web-Based Exercise Programming System Improve Home Exercise Adherence for People With Musculoskeletal Conditions? Am J Phys Med Rehabil. 2019;98(10):850–8. 37. Lustria MLA, Cortese J, Noar SM, Glueckauf RL. Computer-tailored health interventions delivered over the web: Review and analysis of key components. Patient Educ Couns. 2009;74(2):156–73. 38. Fogg BJ. Persuasive Technology: Using computers to change what we think and do. Morgan Kaufmann Publishers; 2003. 39. McGowan A, Sittig S, Bourrie D, Benton R, Iyengar S. The Intersection of Persuasive System Design and Personalization in Mobile Health: Statistical Evaluation. JMIR Mhealth Uhealth. 2022;10(9):e40576. 40. Saleem M, Kühne L, De Santis KK, Christianson L, Brand T, Busse H. Understanding Engagement Strategies in Digital Interventions for Mental Health Promotion: Scoping Review. JMIR Ment Health. 2021;8(12):e30000. 41. Oinas-Kukkonen H, Harjumaa M. Persuasive Systems Design: Key Issues, Process Model, and System Features. Communications of the Association for Information Systems. 2009;24(1):485–500. 42. Bossen D, Kloek C, Snippe HW, Dekker J, de Bakker D, Veenhof C. A Blended Intervention for Patients With Knee and Hip Osteoarthritis in the Physical Therapy Practice: Development and a Pilot Study. JMIR Res Protoc. 2016;5(1):e32.
19 General introduction 43. de Vries HJ, Kloek CJJ, de Bakker DH, Dekker J, Bossen D, Veenhof C. Determinants of Adherence to the Online Component of a Blended Intervention for Patients with Hip and/ or Knee Osteoarthritis: A Mixed Methods Study Embedded in the e-Exercise Trial. Telemed e-Health. 2017;23(12):1002–10. 44. van Gemert-Pijnen JE, Nijland N, van Limburg M, Ossebaard HC, Kelders SM, Eysenbach G, et al. A Holistic Framework to Improve the Uptake and Impact of eHealth Technologies. J Med Internet Res. 2011;13(4):e111. 45. Kloek CJJ, Bossen D, Spreeuwenberg PM, Dekker J, de Bakker DH, Veenhof C. Effectiveness of a Blended Physical Therapist Intervention in People With Hip Osteoarthritis, Knee Osteoarthritis, or Both: A Cluster-Randomized Controlled Trial. Phys Ther. 2018;98(7):560– 70. 46. Kloek CJJ, Van Dongen JM, De Bakker DH, Bossen D, Dekker J, Veenhof C. Costeffectiveness of a blended physiotherapy intervention compared to usual physiotherapy in patients with hip and/or knee osteoarthritis: a cluster randomized controlled trial. BMC Public Health. 2018;18(1):1082. 47. Kloek CJJ, Bossen D, de Vries HJ, de Bakker DH, Veenhof C, Dekker J. Physiotherapists’ experiences with a blended osteoarthritis intervention: a mixed methods study. Physiother Theory Pract. 2020;36(5):572–9. 48. Kloek CJJ, van Tilburg ML, Staal JB, Veenhof C, Bossen D. Development and proof of concept of a blended physiotherapeutic intervention for patients with non-specific low back pain. Physiotherapy. 2019;105(4):483–91. 49. Swart NM, Apeldoorn AT, Conijn D, Meerhoff GA, Ostello RWJG. KNGF-richtlijn lage rugpijn en lumbosacraal radiculair syndroom. KNGF-richtlijn Lage rugpijn en Lumbosacraal radiculair syndroom. 2021. 50. Hill JC, Whitehurst DGT, Lewis M, Bryan S, Dunn KM, Foster NE, et al. Comparison of stratified primary care management for low back pain with current best practice (STarT Back): A randomised controlled trial. Lancet. 2011;378(9802):1560–71. 51. Hill JC, Dunn KM, Lewis M, Mullis R, Main CJ, Foster NE, et al. A primary care back pain screening tool: identifying patient subgroups for initial treatment. Arthritis Rheum. 2008;59(5):632–41. 52. Koppenaal T, Arensman RM, Van Dongen JM, Ostelo RWJG, Veenhof C, Kloek CJJ, et al. Effectiveness and cost-effectiveness of stratified blended physiotherapy in patients with non-specific low back pain: Study protocol of a cluster randomized controlled trial. BMC Musculoskelet Disord. 2020;21(1):1–13. 53. Picha KJ, Howell DM. A model to increase rehabilitation adherence to home exercise programmes in patients with varying levels of self-efficacy. Musculoskeletal Care. 2018;16(1):233–7. 54. Essery R, Geraghty AWA, Kirby S, Yardley L. Predictors of adherence to home-based physical therapies: a systematic review. Disabil Rehabil. 2017;39(6):519–34. 55. Shahidi Id B, Padwal Id J, Lee E, Xu R, Northway S, Taitanoid L, et al. Factors impacting adherence to an exercise-based physical therapy program for individuals with low back pain. PLoS One. 2022;17(10):e0276326. 1
20 Chapter 1 56. Medina-Mirapeix F, Escolar-Reina P, Gascón-Cánovas JJ, Montilla-Herrador J, JimenoSerrano FJ, Collins SM. Predictive factors of adherence to frequency and duration components in home exercise programs for neck and low back pain: an observational study. BMC Musculoskelet Disord. 2009;10(1):155. 57. Areerak K, Waongenngarm P, Janwantanakul P. Factors associated with exercise adherence to prevent or treat neck and low back pain: A systematic review. Musculoskelet Sci Pract. 2021;52:102333. 58. Nicolson PJA, Hinman RS, Kasza J, Bennell KL. Trajectories of adherence to homebased exercise programs among people with knee osteoarthritis. Osteoarthr Cartil. 2018;26(4):513–21. 59. Newman-Beinart NA, Norton S, Dowling D, Gavriloff D, Vari C, Weinman JA, et al. The development and initial psychometric evaluation of a measure assessing adherence to prescribed exercise: the Exercise Adherence Rating Scale (EARS). Physiotherapy. 2017;103(2):180–5. 60. Koppenaal T. e-Exercise Low Back Pain Stratified blended physiotherapy for patients with nonspecific low back pain [dissertation]. [Utrecht]: Utrecht University; 2023.
Chapter 2
Measuring exercise adherence in patients with low back pain: development, validity, and reliability of the EXercise Adherence Scale (EXAS) Remco M. Arensman Rianne H. Geelen Tjarco Koppenaal Cindy Veenhof Martijn F. Pisters Published in Physiotherapy Theory and Practice 2022:38(7):928-937
24 Chapter 2 ABSTRACT Objectives: To develop an instrument to measure adherence to frequency, intensity, and quality of performance of home-based exercise (HBE) programs recommended by a physical therapist and to evaluate its construct validity and reliability in patients with low back pain. Methods: The Exercise Adherence Scale (EXAS) was developed following a literature search, an expert panel review, and a pilot test. The construct validity of the EXAS was determined based on data from 27 participants through an investigation of the convergent validity between adherence, lack of time to exercise, and lack of motivation to exercise. Associations between adherence, pain, and disability were determined to test divergent validity. The reliability of the EXAS quality of performance score was assessed using video recordings from 50 participants performing four exercises. Results: Correlations between the EXAS and lack of time to exercise, lack of motivation to exercise, pain, and disability were rho = 0.47, rho = 0.48, rho = 0.005, and rho = 0.24, respectively. The intrarater reliability of the quality of performance score was Kappa quadratic weights (Kqw) = 0.87 (95%-CI 0.83–0.92). The interrater reliability was Kqw = 0.36 (95%-CI 0.27–0.45). Conclusions: The EXAS demonstrates acceptable construct validity for the measurement of adherence to HBE programs. Additionally, the EXAS shows excellent intrarater reliability and poor interrater reliability for the quality of performance score and is the first instrument to measure adherence to frequency, intensity, and quality of performance of HBE programs. The EXAS allows researchers and clinicians to better investigate the effects of adherence to HBE programs on the outcomes of interventions and treatments.
25 Development of the Exercise Adherence Scale (EXAS) in patients with low back pain BACKGROUND Low back pain (LBP) is a major health problem affecting an estimated 576,989,000 (95% confidence interval: 518,940,400 to 637,177,900) people globally in 2017 (1). LBP has been the leading cause of disability in patients with musculoskeletal disorders since 1990, and its global prevalence has continued to increase (1). From 2012 to 2014, the total aggregate medical costs for spine-related problems were an estimated 315.4 USD billion in the United States of America alone (2). The impact of LBP on patient functioning and the economic burden on society call for effective treatments (3). Previous research has shown that exercise therapy is effective in reducing pain intensity and disability in patients with LBP and is cost-effective when combined with stratified care based on risk prognosis (4,5). These exercise therapy interventions often require patients to adhere to a homebased exercise (HBE) program. Adherence to an HBE program is defined as the extent to which a person’s exercise behavior corresponds with agreed recommendations by a health-care professional (6). These recommendations pertain to frequency (i.e. number of exercise sessions per day or week); intensity (i.e. number of repetitions per exercise session); and quality of performance of the HBE program. Furthermore, in this study, an HBE program is defined as a specific exercise or set of specific exercises recommended by a health-care professional to be completed at home to improve impairments in body functions (e.g. joint mobility, muscle strength, or joint stability). Although HBE programs have been shown to be effective, adherence in patients with LBP varies from approximately 70% to 90% and declines significantly over time (7,8). Additionally, adherence is difficult to assess due to the high rate of socially desirable answers provided by patients using diaries to record adherence, as well as the lack of a clinimetrically tested, standardized measure of exercise adherence (9–12). As a result, the treatment effects of HBE programs on LBP can be underestimated due to poor adherence rates in both research and clinical practice. To better investigate the effects of patient adherence to HBE programs on treatment outcomes, researchers require a reliable and valid measure of adherence (9,10). Additionally, a reliable and valid measure of adherence will allow clinicians to optimize patient adherence to HBE programs and improve treatment outcomes by tailoring treatments to individual patients. For example, strategies to increase self-efficacy, guidance, or exercise attention can be employed to improve low adherence to HBE programs (13,14). Current measures of adherence to HBE programs employ a variety of strategies to measure adherence behavior (9,10,15). Bollen et al. (2014) found 29 questionnaires, 29 diaries, two visual analog scales, and a tally counter (9). Most of these instruments had been used in only one study and lacked clinimetric testing, emphasizing the absence of a reliable, valid, and standardized means to measure adherence behavior (9). Moreover, the existing 2
26 Chapter 2 instruments focus mainly on adherence to frequency and intensity recommendations of HBE programs (15). However, based on findings in patients with osteoarthritis treated by a physical therapist, quality of performance is an important factor in the treatment effects of HBE programs (16). Patients may perform exercises in the exact frequency and intensity recommended by their physical therapist, but if the quality of performance is lacking, the intended effect of the exercise (e.g. muscle strengthening) is far less likely to be achieved. Poor quality of performance of exercises can be especially problematic when trying to assess the effectiveness of HBE programs for the treatment of patients with LBP in both clinical practice and research environments. Unfortunately, there is currently no instrument that can measure adherence to frequency, intensity, and quality of performance recommendations of HBE programs (9,10,15). Therefore, the aims of the current study are to develop an instrument to measure adherence to frequency, intensity, and quality of performance of HBE programs recommended by a health-care professional and to evaluate its construct validity and reliability. METHODS Development This study was performed in primary care physical therapy practices in the Netherlands. In developing the Exercise Adherence Scale (EXAS), the goal was to create an instrument to be used during face-to-face treatment sessions by a physical therapist or other healthcare professionals to record HBE recommendations and patient-reported adherence to HBE recommendations. Furthermore, an observational component for assessing patients’ quality of performance of HBEs was to be included. The resulting instrument measures patient adherence to HBE recommendations from a physical therapist on intensity, frequency, and quality of performance. The instrument was developed using a three-step process consisting of a literature search to create items, a face and content validity check by an expert panel, and a pilot test involving a small sample of patients. In the first step, the literature was searched for studies reporting on adherence to HBE programs, and the tools used to quantify adherence were extracted where possible. The studies found used primarily patient diaries or short questionnaires aimed at quantifying adherence to intensity and frequency recommendations of HBE programs, such as the Sport Injury Rehabilitation Adherence Scale (17). None of the studies found reported on the quality of performance. Based on these findings, the authors created a first draft of the EXAS with a quality of performance component. In the second step, an expert panel comprising researchers from the fields of health-related measurement instrument creation, LBP, and adherence was created.
27 Development of the Exercise Adherence Scale (EXAS) in patients with low back pain The expert panel provided feedback on the relevance and wording of the EXAS and suggested additions where needed in a two-round iterative process, thereby further refining the instrument. In the last step, five physical therapists pilot-tested the EXAS in patients with LBP to ensure that the questions were comprehensible and unambiguous. Based on feedback from the physical therapists and their patients, the final version of the EXAS was produced. The final version of the EXAS is an interview-based instrument with an observational component, completed by the physical therapist together with the patient during each of the patient’s visits (Supplemental File). During the patient’s first treatment session, the physical therapist records the recommendations for the HBE program (i.e. type of exercises, frequency, and intensity) and shares them with the patient. During the patient’s follow-up visits, the physical therapist uses the EXAS to record the frequency and intensity of HBE performance as reported by the patient in a standardized format. Additionally, the physical therapist asks the patient to perform the exercises and rates the quality of performance on a 5-point scale (i.e. poor, moderate, reasonable, good, and excellent). The EXAS contains a qualitative description for the “poor,” “reasonable,” and “excellent” categories to facilitate the rating process (Table 1). Based on the experiences of the physical therapists in the pilot test, completing the EXAS requires approximately five minutes. The EXAS score for the HBE program is calculated in three steps. In step one, the ratio between the frequency and intensity of HBE performance reported by the patient and the corresponding recommendations from the physical therapist is calculated for each exercise and multiplied by 100 to determine the adherence rate [1]. If the patientreported performance of frequency and intensity exceeds therapist recommendations, an adherence rate of 100% is scored instead. Adherence rate = Number of days * number of times per day * sets * repetitions reported by the patient Number of days * number of times per day * sets * repetitions recommended by the therapist) * 100 [1] In step two, the quality of performance score is used to calculate the adherence score for the individual exercise. To obtain the adherence score, the adherence rate for the individual exercise is multiplied by the quality of performance score for the individual exercise [2]. Adherence score=Adherence rate*quality of performance score [2] 2
28 Chapter 2 The quality of performance score depends on the physical therapist’s rating of the patient’s quality of performance of each exercise. Currently, there is no theoretical basis for the impact of the quality of performance on the effectiveness of adherence to HBE recommendations. Therefore, the authors used their clinical experience and experience with instrument development to determine the magnitude of the impact of the quality of performance. In this study, each point on the quality of performance scale reflects 20% effectiveness (Table 1). Table 1 Quality of performance score matrix. Excellent Good Reasonable Moderate Poor Score 1 Score 0.8 Score 0.6 Score 0.4 Score 0.2 All parts of the home-based exercise are performed perfectly according to the recommendations by the therapist. There is no room for improvement. It is certain the desired effect of the exercise has been achieved. Most parts of the exercise are performed well according to the recommendations by the therapist. Important parts of the exercise can be improved. The desired effect of the exercise is likely to have been achieved. The majority or all of the parts of the exercise are not performed according to the recommendations by the therapist. It is very unlikely that the desired effect of the exercise has been achieved. In the third and final step, the EXAS score is obtained by calculating the mean of the adherence scores for all individual exercises in the HBE program [3]. EXAS score = Adherence score exercise 1 + … + Adherence score exercise n n [3] In the clinimetric study, the construct validity and reliability of the EXAS were investigated. Intrarater reliability was assessed only for the quality of the performance rating scale of the EXAS. For both the construct validity and reliability assessments of the EXAS, the physical therapists using the instrument were provided information on the theoretical background of adherence to HBE programs, in addition to receiving training in scoring the EXAS and incorporating the EXAS in clinical practice. Training involved completing the EXAS using data from a test patient and discussing the process with one of the researchers (RA or RG).
29 Development of the Exercise Adherence Scale (EXAS) in patients with low back pain Construct validity Construct validity refers to the extent to which scores obtained with a given measurement instrument relate to scores obtained with other instruments in a manner that is consistent with theoretically derived hypotheses, assuming the measurement instrument validly measures the construct of interest (18). Currently, there is no gold standard for the measurement of adherence to HBE recommendations. Therefore, construct validity was determined by testing convergent and divergent validity using four theoretical hypotheses. Convergent validity is the degree to which a measure correlates with other measures to which it is similar (19). Discriminant (divergent) validity is the degree to which a measure does not correlate with (diverges from) measures that are dissimilar (19). The factor “Barriers” has been found to be the strongest indicator of nonadherence to HBE programs in Dutch patients with LBP (20). Lack of time to exercise and lack of motivation to exercise were among the barriers reported most frequently by patients who did not adhere to HBE recommendations and were chosen for hypothesis testing of convergent validity. Essery, Geraghty, Kirby, and Yardley (2017) reviewed the literature on predictors of adherence to home-based physical therapies and found results for highly varied samples (21). They found that associations between adherence and a variety of possible predictors of adherence ranged mostly from no association to approximately r = 0.50. Therefore, the associations between perceived barriers and adherence were expected to be moderate (r = 0.30 to r = 0.50). Pain and disability were reported as factors by both adherent and nonadherent patients. Therefore, both pain and disability were expected to be unrelated to adherence to HBE recommendations and were chosen to test hypotheses of divergent validity (20). Consequently, the correlations between adherence to HBE recommendations, pain, and disability were expected to be low (r = 0.00 to r = 0.30). The resulting hypotheses to be tested were as follows: 1) The association between lack of time to exercise and the EXAS is between r = 0.30 and r = 0.50; 2) The association between lack of motivation to exercise and the EXAS is between r = 0.30 and r = 0.50; 3) The association between pain and the EXAS is between r = 0.00 and r = 0.30; and 4) The association between disability and the EXAS is between r = 0.00 and r = 0.30. Participants and setting For the validity study, 16 physical therapy primary care practices with 42 physical therapists participated and agreed to recruit patients with LBP according to the following inclusion criteria: the first visit to a physical therapist for the current episode of LBP as the primary complaint, current episode of LBP lasting more than four weeks at the first visit 2
30 Chapter 2 to a physical therapist, between the ages of 20 and 65, and having sufficient command of the Dutch language to read and understand questionnaires and spoken or written instructions. Patients were excluded if they had previously been diagnosed with lumbar radiculopathy, spinal osteoarthritis, or other conditions as the cause of their LBP or if they were unable to perform exercises due to physical or mental issues. Measurements Adherence to HBE. Recommendations were measured with the newly developed EXAS. The EXAS score was calculated using the previously stated assumption of 20% effectiveness for each point on the quality of performance scale. Barriers. The barriers “lack of time to exercise” and “lack of motivation to exercise” were measured using single-item Likert scales based on the barriers subscale used by Sluijs, Kok, and van der Zee (1993) (20). Lack of time to exercise was reported on a 5-point scale ranging from 5 (“always”) to 1 (“never”). Lack of motivation to exercise was measured on a 4-point scale ranging from 1 (“very motivated”) to 4 (“not motivated”). Pain. Pain was measured with the Numeric Rating Scale for pain (NRS Pain) (22–24). Patients were asked to rate the intensity of their current pain on an 11-point numeric scale ranging from 0 (“no pain”) to 10 (“worst pain imaginable”). Disability. Disability was measured with the Dutch language version of the Quebec Back Pain Disability Scale (QBPDS) (25). The QBPDS quantifies disability caused by LBP in daily activities. The questionnaire consists of 20 items, and the total score ranges from 0 (no disability) to 100 (completely restricted). Moderate evidence for positive reliability and validity of the Dutch-language version of the QBPDS has been reported in a review by Speksnijder et al. (2016) (26). Demographics. The following personal and demographic characteristics of the participants were measured: age (in years), gender, height (in centimeters), weight (in kilograms), level of education (i.e. elementary school, high school, vocational school, college, or university), and duration of symptoms (up to 3 months, 3 to 6 months, 6 to 12 months, or more than 12 months). Procedures to test validity All patients with LBP who visited the participating physical therapy practices and agreed to participate were screened for eligibility using the inclusion and exclusion criteria. Written informed consent was obtained from the participants prior to the start of the study. The patients received the usual care, and the physical therapists used the EXAS to record HBE recommendations. Additionally, measurements of pain, disability, barriers, and patient characteristics were completed. One week after the HBE program was recommended to
www.ridderprint.nlRkJQdWJsaXNoZXIy MTk4NDMw