Factors associated with adherence to a supervised exercise intervention for osteoarthritis: Data from the swedish osteoarthritis registry. Battista, S., Kiadaliri, A., Jönsson, T., Gustafsson, K., Englund, M., Testa, M., & Dell'Isola, A. Arthritis Care & Research, 75(10):2117–2126, May, 2023. ![Factors associated with adherence to a supervised exercise intervention for osteoarthritis: Data from the swedish osteoarthritis registry [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Objective. To explore how lifestyle and demographic, socioeconomic, and disease-related factors are associated with supervised exercise adherence in an osteoarthritis (OA) management program and the ability of these factors to explain exercise adherence. Methods. A cohort register-based study on participants from the Swedish Osteoarthritis Registry who attended the exercise part of a nationwide Swedish OA management program. We ran a multinomial logistic regression to determine the association of exercise adherence with the abovementioned factors. We calculated their ability to explain exercise adherence with the McFadden R2. Results. Our sample comprises 19,750 participants (73% female, mean ± SD age 67 ± 8.9 years). Among them, 5,862 (30%) reached a low level of adherence, 3,947 (20%) a medium level, and 9,941 (50%) a high level. After a listwise deletion, the analysis was run on 16,685 participants (85%), with low levels of adherence as the reference category. Some factors were positively associated with high levels of adherence, such as older age (relative risk ratio [RRR] 1.01 [95% confidence interval (95% CI) 1.01–1.02] per year), and the arthritis-specific self-efficacy (RRR 1.04 [95% CI 1.02–1.07] per 10-point increase). Others were negatively associated with high levels of adherence, such as female sex (RRR 0.82 [95% CI 0.75–0.89]), having a medium (RRR 0.89 [95% CI 0.81–0.98] or a high level of education (RRR 0.84 [95% CI 0.76–0.94]). Nevertheless, the investigating factors could explain 1% of the variability in exercise adherence (R2 = 0.012). Conclusion. Despite the associations reported above, the poorly explained variability suggests that strategies based on lifestyle and demographic, socioeconomic, and disease-related factors are unlikely to improve exercise adherence significantly.
@article{battista_factors_2023,
title = {Factors associated with adherence to a supervised exercise intervention for osteoarthritis: {Data} from the swedish osteoarthritis registry},
volume = {75},
issn = {2151-464X, 2151-4658},
shorttitle = {Factors {Associated} {With} {Adherence} to a {Supervised} {Exercise} {Intervention} for {Osteoarthritis}},
url = {https://onlinelibrary.wiley.com/doi/10.1002/acr.25135},
doi = {10.1002/acr.25135},
abstract = {Objective. To explore how lifestyle and demographic, socioeconomic, and disease-related factors are associated with supervised exercise adherence in an osteoarthritis (OA) management program and the ability of these factors to explain exercise adherence.
Methods. A cohort register-based study on participants from the Swedish Osteoarthritis Registry who attended the exercise part of a nationwide Swedish OA management program. We ran a multinomial logistic regression to determine the association of exercise adherence with the abovementioned factors. We calculated their ability to explain exercise adherence with the McFadden R2.
Results. Our sample comprises 19,750 participants (73\% female, mean ± SD age 67 ± 8.9 years). Among them, 5,862 (30\%) reached a low level of adherence, 3,947 (20\%) a medium level, and 9,941 (50\%) a high level. After a listwise deletion, the analysis was run on 16,685 participants (85\%), with low levels of adherence as the reference category. Some factors were positively associated with high levels of adherence, such as older age (relative risk ratio [RRR] 1.01 [95\% confidence interval (95\% CI) 1.01–1.02] per year), and the arthritis-specific self-efficacy (RRR 1.04 [95\% CI 1.02–1.07] per 10-point increase). Others were negatively associated with high levels of adherence, such as female sex (RRR 0.82 [95\% CI 0.75–0.89]), having a medium (RRR 0.89 [95\% CI 0.81–0.98] or a high level of education (RRR 0.84 [95\% CI 0.76–0.94]). Nevertheless, the investigating factors could explain 1\% of the variability in exercise adherence (R2 = 0.012).
Conclusion. Despite the associations reported above, the poorly explained variability suggests that strategies based on lifestyle and demographic, socioeconomic, and disease-related factors are unlikely to improve exercise adherence significantly.},
language = {en},
number = {10},
urldate = {2023-06-07},
journal = {Arthritis Care \& Research},
author = {Battista, Simone and Kiadaliri, Ali and Jönsson, Thérése and Gustafsson, Kristin and Englund, Martin and Testa, Marco and Dell'Isola, Andrea},
month = may,
year = {2023},
pages = {2117--2126},
}
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To explore how lifestyle and demographic, socioeconomic, and disease-related factors are associated with supervised exercise adherence in an osteoarthritis (OA) management program and the ability of these factors to explain exercise adherence. Methods. A cohort register-based study on participants from the Swedish Osteoarthritis Registry who attended the exercise part of a nationwide Swedish OA management program. We ran a multinomial logistic regression to determine the association of exercise adherence with the abovementioned factors. We calculated their ability to explain exercise adherence with the McFadden R2. Results. Our sample comprises 19,750 participants (73% female, mean ± SD age 67 ± 8.9 years). Among them, 5,862 (30%) reached a low level of adherence, 3,947 (20%) a medium level, and 9,941 (50%) a high level. After a listwise deletion, the analysis was run on 16,685 participants (85%), with low levels of adherence as the reference category. Some factors were positively associated with high levels of adherence, such as older age (relative risk ratio [RRR] 1.01 [95% confidence interval (95% CI) 1.01–1.02] per year), and the arthritis-specific self-efficacy (RRR 1.04 [95% CI 1.02–1.07] per 10-point increase). Others were negatively associated with high levels of adherence, such as female sex (RRR 0.82 [95% CI 0.75–0.89]), having a medium (RRR 0.89 [95% CI 0.81–0.98] or a high level of education (RRR 0.84 [95% CI 0.76–0.94]). Nevertheless, the investigating factors could explain 1% of the variability in exercise adherence (R2 = 0.012). Conclusion. Despite the associations reported above, the poorly explained variability suggests that strategies based on lifestyle and demographic, socioeconomic, and disease-related factors are unlikely to improve exercise adherence significantly.","language":"en","number":"10","urldate":"2023-06-07","journal":"Arthritis Care & Research","author":[{"propositions":[],"lastnames":["Battista"],"firstnames":["Simone"],"suffixes":[]},{"propositions":[],"lastnames":["Kiadaliri"],"firstnames":["Ali"],"suffixes":[]},{"propositions":[],"lastnames":["Jönsson"],"firstnames":["Thérése"],"suffixes":[]},{"propositions":[],"lastnames":["Gustafsson"],"firstnames":["Kristin"],"suffixes":[]},{"propositions":[],"lastnames":["Englund"],"firstnames":["Martin"],"suffixes":[]},{"propositions":[],"lastnames":["Testa"],"firstnames":["Marco"],"suffixes":[]},{"propositions":[],"lastnames":["Dell'Isola"],"firstnames":["Andrea"],"suffixes":[]}],"month":"May","year":"2023","pages":"2117–2126","bibtex":"@article{battista_factors_2023,\n\ttitle = {Factors associated with adherence to a supervised exercise intervention for osteoarthritis: {Data} from the swedish osteoarthritis registry},\n\tvolume = {75},\n\tissn = {2151-464X, 2151-4658},\n\tshorttitle = {Factors {Associated} {With} {Adherence} to a {Supervised} {Exercise} {Intervention} for {Osteoarthritis}},\n\turl = {https://onlinelibrary.wiley.com/doi/10.1002/acr.25135},\n\tdoi = {10.1002/acr.25135},\n\tabstract = {Objective. To explore how lifestyle and demographic, socioeconomic, and disease-related factors are associated with supervised exercise adherence in an osteoarthritis (OA) management program and the ability of these factors to explain exercise adherence.\nMethods. A cohort register-based study on participants from the Swedish Osteoarthritis Registry who attended the exercise part of a nationwide Swedish OA management program. We ran a multinomial logistic regression to determine the association of exercise adherence with the abovementioned factors. We calculated their ability to explain exercise adherence with the McFadden R2.\nResults. Our sample comprises 19,750 participants (73\\% female, mean ± SD age 67 ± 8.9 years). Among them, 5,862 (30\\%) reached a low level of adherence, 3,947 (20\\%) a medium level, and 9,941 (50\\%) a high level. After a listwise deletion, the analysis was run on 16,685 participants (85\\%), with low levels of adherence as the reference category. Some factors were positively associated with high levels of adherence, such as older age (relative risk ratio [RRR] 1.01 [95\\% confidence interval (95\\% CI) 1.01–1.02] per year), and the arthritis-specific self-efficacy (RRR 1.04 [95\\% CI 1.02–1.07] per 10-point increase). Others were negatively associated with high levels of adherence, such as female sex (RRR 0.82 [95\\% CI 0.75–0.89]), having a medium (RRR 0.89 [95\\% CI 0.81–0.98] or a high level of education (RRR 0.84 [95\\% CI 0.76–0.94]). Nevertheless, the investigating factors could explain 1\\% of the variability in exercise adherence (R2 = 0.012).\nConclusion. 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