PGSP-Stanford Psy.D. Consortium, United States.
Independent Researcher.
Complement Ther Med. 2018 Oct;40:237-242. doi: 10.1016/j.ctim.2017.11.018. Epub 2017 Dec 2.
Chronic neck pain is a common problem that affects approximately half of the population. Conventional treatments such as medication and exercise have shown limited analgesic effects. This analysis is based on an original study that was conducted to investigate the physical and behavioral effects of a 9-week Iyengar yoga course on chronic non-specific neck pain. This secondary analysis uses linear mixed models to investigate the individual trajectories of pain intensity in participants before, during and after the Iyengar yoga course.
Participants with chronic non-specific neck pain were selected for the study. The participants suffered from neck pain for at least 5 days per week for at least the preceding 3 months, with a mean neck pain intensity (NPI) of 40 mm or more on a Visual Analog Scale of 100 mm. The participants were randomized to either a yoga group (23) or to a self-directed exercise group (24). The mean age of the participants in the yoga group was 46, and ranged from 19 to 59. The participants in the yoga group participated in an Iyengar yoga program designed to treat chronic non-specific neck pain. Our current analysis only includes participants who were initially randomized into the yoga group. The average weekly neck pain intensity at baseline, during and post intervention, comprising 11 total time points, was used to construct the growth models. We performed a step-up linear mixed model analysis to investigate change in NPI during the yoga intervention. We fit nested models using restricted maximum-likelihood estimation (REML), tested fixed effects with Wald test p-values and random effects with the likelihood ratio test. We constructed 10 REML models.
The model that fit the data best was an unconditional random quadratic growth model, with a first-order auto-regressive structure specified for the residual R matrix. Participants in the yoga group showed significant variation in NPI. They demonstrated variation in their intercepts, in their linear rates of change, and most tellingly, in their quadratic rates of change.
While all participants benefitted from the yoga intervention, the degree to which they benefitted varied. Additionally, they did not experience a consistent rate of reduction in NPI - their NPI fluctuated, either increasing and then decreasing, or vice-versa. We comment on the clinical and research implications of our findings.
慢性颈痛是一种常见问题，影响大约一半的人口。传统治疗方法，如药物治疗和运动治疗，显示出有限的镇痛效果。本分析基于一项原始研究，该研究旨在调查为期 9 周的 iyengar 瑜伽课程对慢性非特异性颈痛的身体和行为影响。这项二次分析使用线性混合模型来研究参与者在 iyengar 瑜伽课程前后的疼痛强度的个体轨迹。
选择患有慢性非特异性颈痛的参与者进行研究。参与者每周至少有 5 天颈部疼痛，持续至少 3 个月，颈部疼痛强度（NPI）平均为 40mm 或以上，视觉模拟量表为 100mm。参与者被随机分为瑜伽组（23 人）或自我指导运动组（24 人）。瑜伽组参与者的平均年龄为 46 岁，年龄范围为 19 岁至 59 岁。瑜伽组参与者参加了一项旨在治疗慢性非特异性颈痛的 iyengar 瑜伽项目。我们目前的分析仅包括最初随机分配到瑜伽组的参与者。基线、干预期间和干预后每周平均颈部疼痛强度，包括 11 个总时间点，用于构建增长模型。我们进行了逐步线性混合模型分析，以研究瑜伽干预过程中 NPI 的变化。我们使用受限最大似然估计（REML）拟合嵌套模型，使用 Wald 检验 p 值测试固定效应，使用似然比检验测试随机效应。我们构建了 10 个 REML 模型。
最适合数据的模型是无条件随机二次增长模型，为残差 R 矩阵指定了一阶自回归结构。瑜伽组参与者的 NPI 存在显著差异。他们在截距、线性变化率和最显著的二次变化率方面存在差异。
虽然所有参与者都从瑜伽干预中受益，但受益程度不同。此外，他们的 NPI 没有经历一致的降低率——他们的 NPI 波动，要么增加然后减少，要么反之亦然。我们对研究结果的临床和研究意义进行了评论。
