Stoppok Paula, Teufel Martin, Jahre Lisa, Rometsch Caroline, Müßgens Diana, Bingel Ulrike, Skoda Eva-Maria, Bäuerle Alexander
Clinic for Psychosomatic Medicine and Psychotherapy, LVR-University Hospital Essen, University of Duisburg-Essen, Essen, Germany.
Center for Translational Neuro- and Behavioral Sciences, University of Duisburg-Essen, Essen, Germany.
JMIR Form Res. 2022 Aug 17;6(8):e37682. doi: 10.2196/37682.
Chronic pain is a complex disease with high prevalence rates, and many individuals who are affected do not receive adequate treatment. As a complement to conventional therapies, eHealth interventions could provide many benefits to a multimodal treatment approach for patients with chronic pain, whereby future use is associated with the acceptance of these interventions.
This study aims to assess the acceptance of eHealth pain management interventions among patients with chronic pain and identify the influencing factors on acceptance. A further objective of the study is to evaluate the viability of the Unified Theory of Acceptance and Use of Technology (UTAUT) model and compare it with its extended version in terms of explained variance of acceptance.
We performed a cross-sectional web-based study. In total, 307 participants with chronic pain, as defined according to the International Association for the Study of Pain criteria, were recruited through flyers, posters, and web-based inquiries between December 2020 and July 2021. In addition to sociodemographic and medical data, the assessment included validated psychometric instruments and an extended version of the well-established UTAUT model. For statistical analyses, group comparisons and multiple hierarchical regression analyses were performed.
The acceptance of eHealth pain management interventions among patients with chronic pain was overall moderate to high (mean 3.67, SD 0.89). There was significant difference in acceptance among age groups (W=9674.0; r=0.156; P=.04). Effort expectancy (β=.37; P<.001), performance expectancy (β=.33; P<.001), and social influence (β=.34; P<.001) proved to be the most important predictors of acceptance. The extended UTAUT (including the original UTAUT factors as well as sociodemographic, medical, and eHealth-related factors) model explained 66.4% of the variance in acceptance, thus supporting the viability of the model. Compared with the original UTAUT model (performance expectancy, effort expectancy, and social influence), the extended model explained significantly more variance (F=1.74; P=.02).
Given the association between acceptance and future use, the knowledge of the influencing factors on acceptance should be used in the development and promotion of eHealth pain management interventions. Overall, the acceptance of eHealth pain management interventions was moderate to high. In total, 8 predictors proved to be significant predictors of acceptance. The UTAUT model is a valuable instrument for determining acceptance as well as the factors that influence acceptance of eHealth pain management interventions among patients with chronic pain. The extended UTAUT model provided the greatest predictive value for acceptance.
慢性疼痛是一种患病率很高的复杂疾病，许多患者未得到充分治疗。作为传统疗法的补充，电子健康干预措施可为慢性疼痛患者的多模式治疗方法带来诸多益处，其未来的应用与这些干预措施的接受度相关。
本研究旨在评估慢性疼痛患者对电子健康疼痛管理干预措施的接受度，并确定影响接受度的因素。该研究的另一个目的是评估技术接受与使用统一理论（UTAUT）模型的可行性，并在接受度的解释方差方面将其与扩展版本进行比较。
我们进行了一项基于网络的横断面研究。根据国际疼痛研究协会的标准定义，2020年12月至2021年7月期间，通过传单、海报和网络咨询共招募了307名慢性疼痛参与者。除了社会人口统计学和医学数据外，评估还包括经过验证的心理测量工具和成熟的UTAUT模型的扩展版本。进行了组间比较和多重分层回归分析以进行统计分析。
慢性疼痛患者对电子健康疼痛管理干预措施的接受度总体为中等至高（平均3.67，标准差0.�9）。各年龄组之间的接受度存在显著差异（W = 9674.0；r = 0.156；P = 0.04）。努力期望（β = 0.37；P < .001）、绩效期望（β = 0.33；P < .001）和社会影响（β = 0.34；P < .001）被证明是接受度的最重要预测因素。扩展的UTAUT（包括原始UTAUT因素以及社会人口统计学、医学和电子健康相关因素）模型解释了接受度方差的66.4%，从而支持了该模型的可行性。与原始UTAUT模型（绩效期望、努力期望和社会影响）相比，扩展模型解释的方差显著更多（F = 1.74；P = 0.02）。
鉴于接受度与未来使用之间的关联，在电子健康疼痛管理干预措施的开发和推广中应利用对接受度影响因素的了解。总体而言，电子健康疼痛管理干预措施的接受度为中等至高。共有8个预测因素被证明是接受度的显著预测因素。UTAUT模型是确定慢性疼痛患者对电子健康疼痛管理干预措施的接受度以及影响接受度的因素的有价值工具。扩展的UTAUT模型对接受度提供了最大的预测价值。
