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首页> 外文期刊>Journal of telemedicine and telecare >Predicting post treatment client satisfaction between behavioural activation for depression delivered either in-person or via home-based telehealth
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Predicting post treatment client satisfaction between behavioural activation for depression delivered either in-person or via home-based telehealth

机译:预测抑郁症行为激活之间的治疗后的客户满意度,或者通过家庭远程医疗交付

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摘要

Introduction Treatment engagement, adherence, cancellations and other patient-centric data are important predictors of treatment outcome. But often these data are only examined retrospectively. In this investigation, we analysed data from a clinical trial focused on innovative delivery of depression treatment to identify which patients are likely to prefer either in-home or in-person treatment based on pre-treatment characteristics. Methods Patient satisfaction was assessed in a trial of individuals with depression treated using identical behavioural activation therapy protocols in person or through videoconferencing to the home (N = 87 at post treatment: 42 in-person and 45 in-home participants). The Client Satisfaction Questionnaire was administered at the end of the treatment. A Tobit regression model was used to assess moderation using treatment assignment. Regression lines were generated to model treatment satisfaction as a function of treatment assignment and to identify whether and where the groups intersected. We examined the distributions of the contributing moderators to the subsets of participants above and below the intersection point to identify differences. Results While no significant differences in patient satisfaction were observed between the two groups, or between patients receiving treatment by different providers, baseline characteristics of the sample could be used to differentiate those with a preference for traditional, in-office care from those preferring in-home care. Discussion Participants who were more likely to prefer in-home care were characterized by larger proportions of veterans and lower-ranked enlisted service members. They also had more severe symptoms at baseline and less formal education. Understanding client reactions when selecting treatment modality may allow for a more satisfying patient experience.
机译:引言治疗接合,依从性,取消和其他以患者为中心的数据是治疗结果的重要预测因子。但是,这些数据通常只检查。在这项调查中,我们分析了专注于创新抑郁症治疗的临床试验的数据,以确定哪些患者可能更喜欢基于预处理特征的家庭内或亲自治疗。方法评估患者满意度是否在使用相同的行为激活治疗方案的抑郁症的试验中或通过视频会议对家庭(N = 87在后处理:42个人和45人在家庭参与者中)进行评估。客户满意度问卷在治疗结束时进行。用于使用治疗分配评估适量的Tobit回归模型。生成回归线以模拟处理满意度作为治疗分配的函数,并识别组的群体是否和位置。我们将贡献主持人的分布调查到交叉点之上和下方参与者的子集以确定差异。结果同时两组之间观察到患者满意度没有显着差异,或者在不同提供者接受治疗的患者之间观察到,样品的基线特征可用于区分那些偏好的传统,办公室护理中的那些偏好 - 家庭护理。更有可能更喜欢家庭护理的人的讨论参与者的特点是更大的退伍军人和较低次级的招生服务成员的比例。他们在基线和较少的正规教育中也有更严重的症状。在选择治疗方式时理解客户反应可能允许更满意的患者体验。

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