Pain Management Center, Departments of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
Pain Management Center, Departments of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts.
J Pain. 2019 Mar;20(3):278-287. doi: 10.1016/j.jpain.2018.09.005. Epub 2018 Sep 29.
This study compared persons with chronic pain who consistently reported that their pain was worsening with those who reported that their pain was improving or remaining the same per daily assessment data from a smartphone pain app. All participants completed baseline measures and were asked to record their progress every day by answering whether their overall condition had improved, remained the same, or gotten worse (perceived change) on a visual analogue scale. One hundred forty-four individuals with chronic pain who successfully entered daily assessments were included. Those persons who were classified as worse showed significantly higher pain intensity scores, greater activity interference, higher disability and mood disturbance scores, and higher scores on the Pain Catastrophizing Scale both at baseline and after 3 months (P < .001). Repeated measures analyses and multilevel modeling of perceived change data over different time intervals of 20 assessments over 40 days, 10 assessments over 20 days, and 5 assessments over 10 days were examined. These analyses demonstrated that group classification of better, same, and worse could be reliably determined, even with as few as 5 assessments. These results support the use of innovative mobile health technology to identify individuals who are prone to catastrophize about their pain. Perspective: This study demonstrated that daily assessment of overall perceived change with a smartphone pain app was positively correlated with the Pain Catastrophizing Scale and capturing short-term daily assessment trends data using computer-based classification methods might be a future way to help to identify individuals who tend to catastrophize about their pain.
这项研究比较了慢性疼痛患者，这些患者根据智能手机疼痛应用程序的日常评估数据持续报告疼痛加重，与那些报告疼痛改善或保持不变的患者。所有参与者都完成了基线测量，并被要求通过回答他们的整体状况是否有所改善、保持不变或恶化（感知变化）在视觉模拟量表上，每天记录自己的进展。144 名成功进入日常评估的慢性疼痛患者被纳入研究。那些被归类为更差的患者在基线和 3 个月后表现出显著更高的疼痛强度评分、更大的活动干扰、更高的残疾和情绪困扰评分，以及更高的疼痛灾难化量表评分（P <.001）。对不同时间间隔的感知变化数据进行重复测量分析和多层次建模，包括 40 天内 20 次评估、20 天内 10 次评估和 10 天内 5 次评估。这些分析表明，即使只有 5 次评估，也可以可靠地确定更好、相同和更差的分组分类。这些结果支持使用创新的移动健康技术来识别容易对疼痛产生灾难化认知的个体。观点：这项研究表明，使用智能手机疼痛应用程序对整体感知变化进行日常评估与疼痛灾难化量表呈正相关，并且使用基于计算机的分类方法捕捉短期日常评估趋势数据可能是未来帮助识别容易对疼痛产生灾难化认知的个体的一种方法。
