Cognitive behavioral therapy for chronic pain supported by digital patient feedback and artificial intelligence: Do patients with socioeconomic risk factors benefit?

John D. Piette , Mary A. Driscoll , Eugenia Buta , Robert D. Kerns , Alicia A. Heapy
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引用次数: 0

Abstract

Background

In a recent comparative effectiveness trial, patients with chronic pain receiving cognitive behavioral therapy supported by artificial intelligence and digital feedback (AI-CBT-CP) were more likely to report clinically meaningful improvements in pain-related disability and intensity at six months than patients randomized to standard telephone CBT-CP. Concerns persist about the impact of AI and digital interventions among socially disadvantaged patients. We examined variation in the proportion of patients completing all treatment sessions and reporting clinically meaningful improvements in pain-related disability and intensity across subgroups of patients defined by social determinants of health (SDOH).

Methods

SDOH indicators included age, race, gender, education, income, marital status, geographic access, and clinical severity. Multivariate models with interaction terms tested SDOH indicators as potential moderators of treatment engagement and response to AI-CBT-CP versus standard telephone CBT-CP.

Findings

Roughly half of participants (52.9 %) were 65+ years of age, 10.8 % were women, and 19.1 % reported Black race or multiple racial identities. Relatively favorable session completion was observed among patients randomized to AI-CBT-CP across SDOH subgroup, with no groups more likely to complete all session weeks when receiving standard telephone CBT-CP. The relative benefits of AI-CBT-CP in terms of pain-related disability and intensity were generally confirmed across SDOH subgroups. AI-CBT-CP had a greater relative impact on pain-related disability among patients <65 years old (p = .002). In none of the SDOH subgroups, did standard telephone CBT-CP have a greater impact on pain-related disability or intensity than AI-CBT-CP.

Interpretation

These findings do not suggest that patients with SDOH disadvantages experience poorer treatment engagement or outcomes when offered CBT-CP supported by AI and digital feedback instead of standard telephone CBT-CP. AI-CBT-CP can help overcome treatment access barriers without exacerbating disparities, benefiting underserved populations with chronic pain.

Funding

US Department of Veterans Affairs Health Services Research and Development program.

患者数字反馈和人工智能支持的慢性疼痛认知行为疗法:有社会经济风险因素的患者会受益吗?
背景在最近的一项比较有效性试验中,与随机接受标准电话 CBT-CP 治疗的患者相比,接受人工智能和数字反馈支持的认知行为疗法(AI-CBT-CP)治疗的慢性疼痛患者更有可能在 6 个月后报告疼痛相关的残疾和疼痛强度得到了有临床意义的改善。人工智能和数字化干预对社会弱势群体患者的影响一直令人担忧。我们研究了根据健康的社会决定因素(SDOH)定义的亚组患者中,完成所有治疗疗程并报告疼痛相关残疾和疼痛强度得到有临床意义改善的患者比例的变化情况。方法SDOH指标包括年龄、种族、性别、教育程度、收入、婚姻状况、地理位置和临床严重程度。结果约有一半的参与者(52.9%)年龄在 65 岁以上,10.8% 为女性,19.1% 为黑人或具有多重种族身份。在不同的 SDOH 亚群中,随机接受 AI-CBT-CP 治疗的患者的疗程完成情况相对较好,而接受标准电话 CBT-CP 治疗的患者中,没有任何群体更有可能完成所有疗程。在 SDOH 亚组中,AI-CBT-CP 在疼痛相关残疾和疼痛强度方面的相对优势得到了普遍证实。在 65 岁的患者中,AI-CBT-CP 对疼痛相关残疾的相对影响更大(p = .002)。在 SDOH 亚组中,与 AI-CBT-CP 相比,标准电话 CBT-CP 对疼痛相关残疾或疼痛强度的影响都不大。AI-CBT-CP有助于克服治疗障碍,同时不会加剧差异,从而使服务不足的慢性疼痛人群受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Intelligence-based medicine
Intelligence-based medicine Health Informatics
CiteScore
5.00
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187 days
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