运动恐惧与躯干活动度和疼痛强度相互作用,预测慢性腰背痛患者的残疾情况:分类和回归树(CART)分析。

IF 1.6 4区 医学 Q2 REHABILITATION Physiotherapy Theory and Practice Pub Date : 2024-11-16 DOI:10.1080/09593985.2024.2427273
Fabianna Resende de Jesus-Moraleida, Viviane Rocha Celedonio, Pedro Olavo de Paula Lima, Ana Carla Lima Nunes
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引用次数: 0

摘要

背景:腰背痛严重影响全球健康,尤其是在低收入地区,那里普遍存在初级保健难题。评估与腰背痛相关残疾有关的生物物理和心理因素对于制定有效的筛查和管理策略至关重要:本研究旨在探讨运动恐惧、躯干活动度、疼痛强度、体力活动与腰背痛相关残疾之间的关系,并找出导致慢性腰背痛患者残疾程度较高的关键因素:这项横断面研究分析了 381 名 18 岁以上慢性腰背痛患者的数据,这些数据是 2015 年至 2019 年期间在一家初级保健门诊收集的。测量的变量包括疼痛强度、运动恐惧、体力活动、躯干活动度和残疾程度。采用分类和回归树方法对残疾预测因素进行建模:运动恐惧是导致高残疾率的主要因素(OR = 17.3,95%CI 8.9-33.7)。有两种情况特别容易导致较高的残疾率:高度恐惧运动(>47.5)且疼痛强度>1.5的患者;恐惧运动程度较低但躯干活动能力较差(>36.5 厘米)的患者。躯干活动能力较好、疼痛强度较低(≤3.5)的患者残疾程度明显较低(OR = 0.06,95%CI 0.02-0.17):研究结果突出表明,在管理慢性腰背痛时,需要更好地整合心理和生物物理评估。了解对运动的恐惧、躯干活动度和疼痛之间的相互影响,可以提高筛查的准确性,并在资源有限的环境中优化护理,在这些情况下使用有效可行的工具。
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Fear of movement interacts with trunk mobility, and pain intensity to predict disability in patients with chronic low back pain: a classification and regression tree (CART) analysis.

Background: Low back pain significantly impacts global health, particularly in low-income areas where primary care challenges are prevalent. Assessing both biophysical and psychological factors associated with low back pain-related disability is crucial for developing effective screening and management strategies.

Objectives: This study aimed to examine the association between fear of movement, trunk mobility, pain intensity, physical activity, and low back pain-related disability, and to identify key factors contributing to higher disability levels in patients with chronic low back pain.

Methods: This cross-sectional study analyzed data from 381 chronic low back pain patients aged over 18, collected at a primary care ambulatory between 2015 and 2019. Variables measured included pain intensity, fear of movement, physical activity, trunk mobility, and disability. A Classification and Regression Tree approach was used to model disability predictors.

Results: Fear of movement was the main driver of high disability (OR = 17.3, 95%CI 8.9-33.7). Two profiles were particularly prone to higher disability: patients with high fear of movement (>47.5) and pain intensity > 1.5; and those with lower fear of movement but poor trunk mobility (>36.5 cm). Patients with better trunk mobility and low pain intensity (≤3.5) showed significantly less disability (OR = 0.06, 95%CI 0.02-0.17).

Conclusions: The findings highlight the need for integrating better psychological and biophysical assessments in managing chronic low back pain. Understanding how fear of movement, trunk mobility, and pain interaction can improve screening accuracy and optimize care in resource-limited settings, using valid and feasible tools for these scenarios.

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来源期刊
CiteScore
3.40
自引率
10.00%
发文量
300
期刊介绍: The aim of Physiotherapy Theory and Practice is to provide an international, peer-reviewed forum for the publication, dissemination, and discussion of recent developments and current research in physiotherapy/physical therapy. The journal accepts original quantitative and qualitative research reports, theoretical papers, systematic literature reviews, clinical case reports, and technical clinical notes. Physiotherapy Theory and Practice; promotes post-basic education through reports, reviews, and updates on all aspects of physiotherapy and specialties relating to clinical physiotherapy.
期刊最新文献
Investigation of pain activity patterns, disability, body awareness, proprioception and function in individuals with and without lumbar spinal decompression surgery. Variation in amyotrophic lateral sclerosis presentation and outcomes based on phenotype and physical therapy movement system diagnosis: a case series. The prevalence, characteristics, and associated factors of pain in individuals with and without chronic obstructive pulmonary disease. Association between varus thrust and foot alignment and flexibility in knee osteoarthritis. Fear of movement interacts with trunk mobility, and pain intensity to predict disability in patients with chronic low back pain: a classification and regression tree (CART) analysis.
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