#PAGE_PARAMS# #ADS_HEAD_SCRIPTS# #MICRODATA#

Validation of the Czech version of the Patterns of Activity Measure – Pain in patients with chronic low back pain


Authors: L. Sikorová 1;  A. Polanská 2;  R. Zoubková 1;  A. Mátlová 1;  J. Divák 1;  M. Parma 1
Authors‘ workplace: Centrum léčby bolesti, Klinika anesteziologie, resuscitace a intenzivní medicíny, FN Ostrava 1;  Útvar náměstka ředitele pro ošetřovatelskou péči, FN Ostrava 2
Published in: Cesk Slov Neurol N 2025; 88(6): 365-372
Category: Original Paper
doi: https://doi.org/10.48095/cccsnn2025365

Overview

Objective: The aim of this study was to translate and validate the psychometric properties of the Patterns of Activity Measure –⁠ Pain in the Czech language. This tool assesses behavioral patterns related to physical activity in patients with chronic pain. As no validated instrument of this kind currently exists in the Czech context, the adaptation of the assessment tool represents an important contribution to diagnostic assessment and the individualization of therapeutic interventions in this population. Methods: A total of 151 patients (18–65 years) with chronic low back pain were included in the study. The instrument was linguistically adapted following international guidelines. Subsequently, exploratory and confirmatory factor analyses were conducted. Internal consistency was evaluated using Cronbach’s alpha, and convergent and concurrent validity were assessed through correlations with other validated instruments. Results: A three-factor structure of the tool (avoidance, overdoing, and activity pacing) was confirmed. The final confirmatory factor analysis model, after removing three items, showed an acceptable model fit. Internal consistency for the domains ranged from 0.89 to 0.94. Convergent and concurrent validity were supported by correlations with pain intensity, quality of life, psychological distress, and physical activity level. Conclusions: The Czech version of the Patterns of Activity Measure –⁠ Pain demonstrates good psychometric properties and can be considered as a reliable instrument for both clinical and research use in assessing activity-related behavioral patterns in patients with chronic low back pain.

Keywords:

Psychometrics – validation study – pain measurement – low back pain – activity pacing


Sources

1. Alfalogy E, Mahfouz S, Elmedany S et al. Chronic low back pain: prevalence, impact on quality of life, and predictors of future disability. Cureus 2023; 15 (9): e45760. doi: 10.7759/cureus.45760.

2. GBD 2021 Low Back Pain Collaborators. Global, regional, and national burden of low back pain, 1990-2020, its attributable risk factors, and projections to 2050: a systematic analysis of the global burden of disease study 2021. Lancet Rheumatol 2023; 5 (6): e316–e329. doi: 10.1016/S2665-9913 (23) 00098-X.

3. Cane D, Nielson WR, McCarthy M et al. Pain-related activity patterns: measurement, interrelationships, and associations with psychosocial functioning. Clin J Pain 2013; 29 (5): 435–442. doi: 10.1097/AJP.0b013e3182 5e452f.

4. Antcliff D, Keenan AM, Keeley P et al. Pacing does help you get your life back: the acceptability of a newly developed activity pacing framework for chronic pain/fatigue. Musculoskeletal Care 2021; 20 (1): 99–110. doi: 10.1002/msc.1557.

5. Suygun ET, Celenay ST. Turkish translation of the patterns of activity measure-pain in patients with chronic low back and neck pain: validity and reliability. Pain Manag Nurs 2022; 23 (2): 231–236. doi: 10.1016/ j.pmn.2021.01.008.

6. Barakou I, Hackett KL, Finch T et al. Self-regulation of effort for a better health-related quality of life: a multidimensional activity pacing model for chronic pain and fatigue management. Ann Med 2023; 55 (2): 2270688. doi: 10.1080/07853890.2023.2270688.

7. Rita M, Leah R, Jürgen D et al. Frequencies of persistence, activity pacing, fear avoidance and general stress in acute neck pain. Compr Psychoneuroendocrinol 2025; 23 (23): 100308. doi: 10.1016/j.cpnec.2025. 100308.

8. Hartvigsen J, Hancock MJ, Kongsted A et al. What low back pain is and why we need to pay attention. Lancet 2018; 391 (10137): 2356–2367. doi: 10.1016/S0140-6736 (18) 30480-X.

9. Cane D, Nielson WR, Mazmanian et al. Patterns of activity in patients with chronic pain: psychometric properties of the patterns of activity measure-pain (POAM-P). Pain 2013; 154 (2): 277–284. doi: 10.1016/ j.pain.2012.10.004.

10. Kindermans HP, Roelofs J, Goossens ME et al. Activity patterns in chronic pain: underlying dimensions and associations with disability and depressed mood. J Pain 2011; 12 (10): 1049–1058. doi: 10.1016/j.jpain.2011. 04.009.

11. Enomoto K, Adachi T, Mibu A et al. Validation of the japanese version of the patterns af aktivity measure-pain in individuals with chronic pain. BioPsychoSocial Med 2022; 16 (1): 19. doi: 10.1186/s13030–13022 –⁠ 00248–z.

12. MacCallum RC, Widaman KF, Zhang S et al. Sample size in factor analysis. Psychol Methods 1999; 4 (1): 84–99. doi: 10.1037/1082–1989X.4.1.84.

13. Wild D, Grove A, Martin M et al. Principles of good practice for the translation and cultural adaptation process for patient-reported outcomes (PRO) measures: report of the ISPOR task force for translation and cultural adaptation. Value Health 2005; 8 (2): 94–104. doi: 10.1111/j.1524-4733.2005.04054.x.

14. Bužgová R, Hajnová E, Feltl D et al. Faktory ovlivňující úzkost a depresi u pacientů v konečném stadiu nemoci při hospitalizaci. Čes a slov Psychiatr 2014; 110 (5): 243–249.

15. Dragomirecká E, Bartoňová J. WHOQOL-BREF. WHOQOL-100. Příručka pro uživatele české verze dotazníků kvality života Světové zdravotnické organizace. 1. vyd. Praha: Psychiatrické centrum Praha 2006.

16. Guidelines for Data Processing and Analysis of the International Physical Activity Questionnaire (IPAQ) –⁠ Short and Long Forms. [online]. Available form: https: //www.academia.edu.

17. Dušek L, Pavlík T, Jarkovský J et al. Analýza dat v neurologii XXIX. Spolehlivost (reliabilita) klinických testů. Cesk Slov Neurol N 2011; 74/107 (5): 594–599.

18. Thompson B. Exploratory and confirmatory factor analysis: understanding concepts and applications. [online]. Available from: https: //psycnet.apa.org/PsycBOOKS/toc/10694.

19. West SG, Taylor AB, Wu W. Model fit and model selection in structural equation modeling. In: Hoyle RH (ed). 1st ed. Handbook of structural equation modeling. New York: The Guilford Press 2012 : 209–231.

20. Benaim C, Léger B, Vuistiner P et al. Validation of the french version of the “Patterns of Activity Measure” in patients with chronic musculoskeletal pain. Pain Res Manag 2017; 2017 : 6570394. doi: 10.1155/2017/6570394.

21. Nielson WR, Jensen MP, Karsdorp PA et al. Activity pacing in chronic pain: concepts, evidence, and future directions. Clin J Pain 2013; 29 (5): 461–468. doi: 10.1097/AJP.0b013e3182608561.

22. Kavka T, Ryšavá M, Kobesová A. Clinicians’ adherence to low back pain guidelines in the Czech Republic is low –⁠ an exploratory cross-sectional study. Cesk Slov Neurol N 2024; 87/120 (6): 408–416. doi: 10.48095/cccsnn2024408.

23. Vlaeyen JWS, Linton SJ. Fear-avoidance and its consequences in chronic musculoskeletal pain: a state of the art. Pain 2000; 85 (3): 317–332. doi: 10.1016/S0304-3959 (99) 00242-0.

24. Louw A, Diener I, Butler DS et al. The effect of neuroscience education on pain, disability, anxiety, and stress in chronic musculoskeletal pain. Arch Phys Med Rehabil 2011; 92 (12): 2041–2056. doi: 10.1016/j.apmr.2011.07.198.

Labels
Paediatric neurology Neurosurgery Neurology

Article was published in

Czech and Slovak Neurology and Neurosurgery

Issue 6

2025 Issue 6
Popular this week
Most read in this issue
Login
Forgotten password

Enter the email address that you registered with. We will send you instructions on how to set a new password.

Login

Don‘t have an account?  Create new account

#ADS_BOTTOM_SCRIPTS#