The Mediation Effect of Pain on the Relationship between Kinesiophobia and Lumbar Joint Position Sense in Chronic Low Back Pain Individuals: A Cross-Sectional Study

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Abstract

(1) Background: Fear of movement (kinesiophobia) and impaired lumbar joint position sense (LJPS) play a vital role in developing and maintaining non-specific chronic low back pain (CLBP). However, how kinesiophobia impacts LJPS is still being determined. The aims of this study are to (1) assess the correlation between kinesiophobia and LJPS in individuals with chronic low back pain; (2) compare LJPS between individuals with CLBP and those who are asymptomatic; and (3) evaluate if pain can mediate the relationship between kinesiophobia and LJPS in CLBP individuals. (2) Methods: Eighty-three individuals (mean age = 48.9 ± 7.5 years) with a diagnosis of CLBP and 95 asymptomatic individuals (mean age = 49.4 ± 7.0 years) were recruited into this cross-sectional study. Fear of movement in CLBP individuals was assessed using the Tampa Scale for Kinesiophobia (TSK). LJPS was determined using the active target repositioning technique using a dual-digital inclinometer. LJPS was evaluated in lumbar flexion, extension, and side-bending left and right directions, and the repositioning accuracy was determined in degrees using a dual digital inclinometer. (3) Results: Kinesiophobia showed a significant (p < 0.001) moderate positive correlation with LJPS (flexion: r = 0.51, extension: r = 0.41, side-bending left: r = 0.37 and side-bending right: r = 0.34). LJPS errors were larger in CLBP individuals compared to asymptomatic individuals (p < 0.05). Mediation analyses showed that pain significantly mediated the relationship between kinesiophobia and LJPS (p < 0.05) in CLBP individuals. (4) Conclusions: Kinesiophobia and LJPS were positively associated. LJPS is impaired in CLBP individuals compared to asymptomatic individuals. Pain may mediate adverse effects on LJPS. These factors must be taken into account when assessing and developing treatment plans for those with CLBP.

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Fear of movement/(re)injury in chronic low back pain and its relation to behavioral performance.

Johan W S Vlaeyen, Ank Kole-Snijders, Ruben G B Boeren … (1995)

Two studies are presented that investigated 'fear of movement/(re)injury' in chronic musculoskeletal pain and its relation to behavioral performance. The 1st study examines the relation among fear of movement/(re)injury (as measured with the Dutch version of the Tampa Scale for Kinesiophobia (TSK-DV)) (Kori et al. 1990), biographical variables (age, pain duration, gender, use of supportive equipment, compensation status), pain-related variables (pain intensity, pain cognitions, pain coping) and affective distress (fear and depression) in a group of 103 chronic low back pain (CLBP) patients. In the 2nd study, motoric, psychophysiologic and self-report measures of fear are taken from 33 CLBP patients who are exposed to a single and relatively simple movement. Generally, findings demonstrated that the fear of movement/(re)injury is related to gender and compensation status, and more closely to measures of catastrophizing and depression, but in a much lesser degree to pain coping and pain intensity. Furthermore, subjects who report a high degree of fear of movement/(re)injury show more fear and escape/avoidance when exposed to a simple movement. The discussion focuses on the clinical relevance of the construct of fear of movement/(re)injury and research questions that remain to be answered.

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A review of psychological risk factors in back and neck pain.

S J Linton (2000)

The literature on psychological factors in neck and back pain was systematically searched and reviewed. To summarize current knowledge concerning the role of psychological variables in the etiology and development of neck and back pain. Recent conceptions of spinal pain, especially chronic back pain, have highlighted the role of psychological factors. Numerous studies subsequently have examined the effects of various psychological factors in neck and back pain. There is a need to review this material to ascertain what conclusions may be drawn. Medical and psychological databases and cross-referencing were used to locate 913 potentially relevant articles. A table of 37 studies was constructed, consisting only of studies with prospective designs to ensure quality. Each study was reviewed for the population studied, the psychological predictor variables, and the outcome. The available literature indicated a clear link between psychological variables and neck and back pain. The prospective studies indicated that psychological variables were related to the onset of pain, and to acute, subacute, and chronic pain. Stress, distress, or anxiety as well as mood and emotions, cognitive functioning, and pain behavior all were found to be significant factors. Personality factors produced mixed results. Although the level of evidence was low, abuse also was found to be a potentially significant factor. Psychological factors play a significant role not only in chronic pain, but also in the etiology of acute pain, particularly in the transition to chronic problems. Specific types of psychological variables emerge and may be important in distinct developmental time frames, also implying that assessment and intervention need to reflect these variables. Still, psychological factors account for only a portion of the variance, thereby highlighting the multidimensional view. Because the methodologic quality of the studies varied considerably, future research should focus on improving quality and addressing new questions such as the mechanism, the developmental time factor, and the relevance that these risk factors have for intervention.

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Sample size determination and power analysis using the G*Power software

Hyun Kang (2021)

Appropriate sample size calculation and power analysis have become major issues in research and publication processes. However, the complexity and difficulty of calculating sample size and power require broad statistical knowledge, there is a shortage of personnel with programming skills, and commercial programs are often too expensive to use in practice. The review article aimed to explain the basic concepts of sample size calculation and power analysis; the process of sample estimation; and how to calculate sample size using G*Power software (latest ver. 3.1.9.7; Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany) with 5 statistical examples. The null and alternative hypothesis, effect size, power, alpha, type I error, and type II error should be described when calculating the sample size or power. G*Power is recommended for sample size and power calculations for various statistical methods (F, t, χ 2 , Z, and exact tests), because it is easy to use and free. The process of sample estimation consists of establishing research goals and hypotheses, choosing appropriate statistical tests, choosing one of 5 possible power analysis methods, inputting the required variables for analysis, and selecting the “calculate” button. The G*Power software supports sample size and power calculation for various statistical methods (F, t, χ 2 , z, and exact tests). This software is helpful for researchers to estimate the sample size and to conduct power analysis.