Factors associating with disability of non-specific low back pain in different subgroups: A hierarchical linear regression analysis

Abstract

This study aimed to explore factors associating with disability, which means physical impairment affecting a person’s mobility, capacity, stamina, or agility, of non-specific low back pain (NSLBP) of the acute and non-acute groups. Two hundred thirty-five patients with NSLBP of less than 8 weeks’ duration as acute groups (n = 124) and more than 8 weeks’ duration as non-acute group (n = 111) were recruited. It was collected data on pain intensity, disability and psychosocial factors, including pain catastrophising, fear of movement and pain self-efficacy. Disability was measured Roland Morris Disability Questionnaire. A hierarchical multiple regression analysis was performed to analyse factors associating with disability of the acute and non-acute groups. The Result was that explanatory power increased with each additional variable of the order of demographic characteristics, pain intensity and psychosocial factors for both groups. Pain intensity, pain catastrophising and pain self-efficacy had significant explanatory power, with pain self-efficacy having the most significant association on the acute group. Only pain self-efficacy having the most significant association on disability of the non-acute group. In conclusion, the factors associating with disability differed depending on the duration of the disease, and pain self-efficacy might be one of the factors associating with disability of patients with NSLBP.

The relationships between pain‐associated psychological distress, pain intensity, patient expectations, and physical function in individuals with musculoskeletal pain: A retrospective cohort study

“…PAPD can also account for a portion of the variance in physical function at discharge scores, although this was identified only in the subgroup of patients with low back pain in this current study. Although these findings were similar to what has been published previously, the proportion of explained variance was smaller in this cohort 27,51–54,56–58 . This may be because other studies often employ greater control in their designs to maximize internal consistency, whereas this cohort used routinely collected data.…”

“…Although these findings were similar to what has been published previously, the proportion of explained variance was smaller in this cohort. 27,[51][52][53][54][56][57][58] This may be because other studies often employ greater control in their designs to maximize internal consistency, whereas this cohort used routinely collected data.…”

Artificial Intelligence‐Enabled Sensing Technologies in the 5G/Internet of Things Era: From Virtual Reality/Augmented Reality to the Digital Twin

“…The ultimate goal is to use various AI methods to make predictions in highly complex systems, such as predicting machine failures, sensor service life, gas concentration changes, and so on. [254][255][256] For instance, Wertheim et al use the regression analysis to estimate the effect of viral load on clustering to provide an approximation of the impact of higher viral load on transmission fitness in the reconstructed HIV genetic transmission clusters. [257] Angenent-Mari et al use multilayer perceptron (MLP) to build a comprehensive regression model to predict toehold switch function as a canonical riboswitch model in synthetic biology.…”

The association between disability and physical performance, pain intensity, and pain-related anxiety in patients after lumbar decompression surgery: a cross-sectional study

“…Disability is a core issue in LBP, affecting physical performance and aerobic fitness [ 4 ]. Many factors such as psychosocial factors, pain intensity, and functional capacity, are reported to be related to disability in LBP individuals [ 5 – 7 ]. Psychological factors such as high levels of pain-related anxiety are recognized as a predisposing factor for avoiding physical activity, which leads to disability development and pain maintenance [ 5 ].…”