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预测混合式认知行为疗法干预中护理的未启动和退出情况:早期数字参与、社会人口学因素和临床因素的影响

Predicting non-initiation of care and dropout in a blended care CBT intervention: Impact of early digital engagement, sociodemographic, and clinical factors.

作者信息

Wu Monica S, Chen Shih-Yin, Wickham Robert E, Leykin Yan, Varra Alethea, Chen Connie, Lungu Anita

机构信息

Lyra Health, Burlingame, USA.

Department of Psychological Sciences, Northern Arizona University, Flagstaff, USA.

出版信息

Digit Health. 2022 Oct 26;8:20552076221133760. doi: 10.1177/20552076221133760. eCollection 2022 Jan-Dec.

Abstract

OBJECTIVE

This study examines predictors of non-initiation of care and dropout in a blended care CBT intervention, with a focus on early digital engagement and sociodemographic and clinical factors.

METHODS

This retrospective cohort analysis included 3566 US-based individuals who presented with clinical levels of anxiety and depression and enrolled in a blended-care CBT (BC-CBT) program. The treatment program consisted of face-to-face therapy sessions via videoconference and provider-assigned digital activities that were personalized to the client's presentation. Multinomial logistic regression and Cox proportional hazard survival analysis were used to identify predictors of an increased likelihood of non-initiation of therapy and dropout.

RESULTS

Individuals were more likely to cancel and/or no-show to their first therapy session if they were female, did not disclose their ethnicity, reported poor financial status, did not have a college degree, endorsed more presenting issues during the onboarding triage assessment, reported taking antidepressants, and had a longer wait time to their first appointment. Of those who started care, clients were significantly more likely to drop out if they did not complete the digital activities assigned by their provider early in treatment, were female, reported more severe depressive symptoms at baseline, reported taking antidepressants, and did not disclose their ethnicity.

CONCLUSIONS

Various sociodemographic and clinical predictors emerged for both non-initiation of care and for dropout, suggesting that clients with these characteristics may benefit from additional attention and support (especially those with poor early digital engagement). Future research areas include targeted mitigation efforts to improve initiation rates and curb dropout.

摘要

目的

本研究探讨混合式认知行为疗法(CBT)干预中未开始治疗及退出治疗的预测因素,重点关注早期数字参与度以及社会人口学和临床因素。

方法

这项回顾性队列分析纳入了3566名美国患者,这些患者存在临床水平的焦虑和抑郁,并参加了混合式认知行为疗法(BC - CBT)项目。治疗方案包括通过视频会议进行的面对面治疗课程以及根据患者情况定制的由治疗师指定的数字活动。采用多项逻辑回归和Cox比例风险生存分析来确定未开始治疗和退出治疗可能性增加的预测因素。

结果

如果患者为女性、未披露种族、报告财务状况不佳、没有大学学位、在入职分诊评估中提出更多问题、报告正在服用抗抑郁药以及首次预约等待时间较长,那么他们更有可能取消和/或未参加首次治疗课程。在开始治疗的患者中,如果他们在治疗早期未完成治疗师分配的数字活动、为女性、基线时报告有更严重的抑郁症状、报告正在服用抗抑郁药以及未披露种族,则退出治疗的可能性显著更高。

结论

未开始治疗和退出治疗均出现了各种社会人口学和临床预测因素,这表明具有这些特征的患者可能会从额外的关注和支持中受益(尤其是那些早期数字参与度较低的患者)。未来的研究领域包括有针对性的缓解措施,以提高开始治疗率并减少退出治疗的情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c2d8/9608016/726d1d3019fb/10.1177_20552076221133760-fig1.jpg

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