Janela Dora, Tong Xin, Areias Anabela C, Pires Diogo, Costa Fabíola, Fonseca Hélder
Sword Health, Inc, Draper, UT, USA.
Faculty of Sport, University of Porto, Porto, Portugal.
Pain Rep. 2025 Aug 20;10(5):e1319. doi: 10.1097/PR9.0000000000001319. eCollection 2025 Oct.
BACKGROUND: Despite compelling evidence identifying psychological predictive factors in in-person rehabilitation, their validity in remote digital care settings remains unknown. OBJECTIVE: To assess whether fear-avoidance beliefs, depression, and anxiety predict pain outcomes after a digital care program (DCP) for chronic musculoskeletal pain (CMP). METHODS: This ad hoc analysis of a decentralized interventional investigation included patients with CMP who underwent a DCP integrating exercise, education, and behavioral change. Pain outcomes were assessed using 4 measures: last pain score, relative pain change, achievement of postintervention mild pain, and pain response (≥30% change or last pain score ≤3). Predictors included baseline scores of Fear-avoidance Beliefs Questionnaire related to Physical Activity, Patient Health 9-item Questionnaire, and Generalized Anxiety Disorder 7-item scale. Structural equation models evaluated their predictive value on pain outcomes, with or without including potential demographic and clinical confounders. RESULTS: Fear-avoidance beliefs and depression symptoms were consistent predictors across all pain outcomes after confounders adjustment. Worse outcomes were associated with higher baseline fear-avoidance beliefs (eg, last pain score: β = 0.15, SE 0.04, < 0.001; pain response: odds ratio [OR] 0.86, 95% confidence interval [CI] 0.78; 0.96, = 0.001) and depression levels (eg, last pain score: β = 0.14, SE 0.05, = 0.007; pain response: OR 0.85, 95% CI 0.74; 0.98, = 0.008). Anxiety did not significantly affect any pain outcome. Sensitivity analyses showed stronger predictive performance when psychological factors were combined with clinical characteristics. CONCLUSIONS: Fear-avoidance beliefs and depression consistently predicted pain outcomes, reinforcing their critical role in digital rehabilitation for CMP. Multimodal, tailored approaches targeting these factors may optimize recovery in remote care.
背景:尽管有确凿证据表明在面对面康复中存在心理预测因素,但其在远程数字护理环境中的有效性仍不明确。 目的:评估恐惧回避信念、抑郁和焦虑是否能预测慢性肌肉骨骼疼痛(CMP)数字护理计划(DCP)后的疼痛结果。 方法:这项对分散式干预调查的临时分析纳入了接受包含运动、教育和行为改变的DCP的CMP患者。使用4种测量方法评估疼痛结果:末次疼痛评分、相对疼痛变化、干预后达到轻度疼痛以及疼痛反应(变化≥30%或末次疼痛评分≤3)。预测因素包括与身体活动相关的恐惧回避信念问卷、患者健康9项问卷和广泛性焦虑障碍7项量表的基线评分。结构方程模型评估了它们对疼痛结果的预测价值,包括或不包括潜在的人口统计学和临床混杂因素。 结果:在调整混杂因素后,恐惧回避信念和抑郁症状是所有疼痛结果的一致预测因素。更差的结果与更高的基线恐惧回避信念(例如,末次疼痛评分:β = 0.15,标准误0.04,P < 0.001;疼痛反应:比值比[OR] 0.86,95%置信区间[CI] 0.78;0.96,P = 0.001)和抑郁水平(例如,末次疼痛评分:β = 0.14,标准误0.05,P = 0.007;疼痛反应:OR 0.85,95% CI 0.74;0.98,P = 0.008)相关。焦虑并未显著影响任何疼痛结果。敏感性分析表明,当心理因素与临床特征相结合时,预测性能更强。 结论:恐惧回避信念和抑郁一致地预测了疼痛结果,强化了它们在CMP数字康复中的关键作用。针对这些因素的多模式、个性化方法可能会优化远程护理中的康复效果。
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