Suharwardy Sanaa, Ramachandran Maya, Leonard Stephanie A, Gunaseelan Anita, Lyell Deirdre J, Darcy Alison, Robinson Athena, Judy Amy
Department of Obstetrics and Gynecology, Division of Maternal Fetal Medicine and Obstetrics, Stanford University, Stanford, CA (Dr. Suharwardy, Dr. Ramachandran, Dr. Leonard, Dr Gunaseelan, Dr Lyell, and Dr Judy).
Woebot Health, San Francisco, CA (Drs Darcy and Robinson).
AJOG Glob Rep. 2023 Mar 29;3(3):100165. doi: 10.1016/j.xagr.2023.100165. eCollection 2023 Aug.
Perinatal mood disorders are common yet underdiagnosed and un- or undertreated. Barriers exist to accessing perinatal mental health services, including limited availability, time, and cost. Automated conversational agents (chatbots) can deliver evidence-based cognitive behavioral therapy content through text message-based conversations and reduce depression and anxiety symptoms in select populations. Such digital mental health technologies are poised to overcome barriers to mental health care access but need to be evaluated for efficacy, as well as for preliminary feasibility and acceptability among perinatal populations.
To evaluate the acceptability and preliminary efficacy of a mental health chatbot for mood management in a general postpartum population.
An unblinded randomized controlled trial was conducted at a tertiary academic center. English-speaking postpartum women aged 18 years or above with a live birth and access to a smartphone were eligible for enrollment prior to discharge from delivery hospitalization. Baseline surveys were administered to all participants prior to randomization to a mental health chatbot intervention or to usual care only. The intervention group downloaded the mental health chatbot smartphone application with perinatal-specific content, in addition to continuing usual care. Usual care consisted of routine postpartum follow up and mental health care as dictated by the patient's obstetric provider. Surveys were administered during delivery hospitalization (baseline) and at 2-, 4-, and 6-weeks postpartum to assess depression and anxiety symptoms. The primary outcome was a change in depression symptoms at 6-weeks as measured using two depression screening tools: Patient Health Questionnaire-9 and Edinburgh Postnatal Depression Scale. Secondary outcomes included anxiety symptoms measured using Generalized Anxiety Disorder-7, and satisfaction and acceptability using validated scales. Based on a prior study, we estimated a sample size of 130 would have sufficient (80%) power to detect a moderate effect size (d=.4) in between group difference on the Patient Health Questionnaire-9.
A total of 192 women were randomized equally 1:1 to the chatbot or usual care; of these, 152 women completed the 6-week survey (n=68 chatbot, n=84 usual care) and were included in the final analysis. Mean baseline mental health assessment scores were below positive screening thresholds. At 6-weeks, there was a greater decrease in Patient Health Questionnaire-9 scores among the chatbot group compared to the usual care group (mean decrease=1.32, standard deviation=3.4 vs mean decrease=0.13, standard deviation=3.01, respectively). 6-week mean Edinburgh Postnatal Depression Scale and Generalized Anxiety Disorder-7 scores did not differ between groups and were similar to baseline. 91% (n=62) of the chatbot users were satisfied or highly satisfied with the chatbot, and 74% (n=50) of the intervention group reported use of the chatbot at least once in 2 weeks prior to the 6-week survey. 80% of study participants reported being comfortable with the use of a mobile smartphone application for mood management.
Use of a chatbot was acceptable to women in the early postpartum period. The sample did not screen positive for depression at baseline and thus the potential of the chatbot to reduce depressive symptoms in this population was limited. This study was conducted in a general obstetric population. Future studies of longer duration in high-risk postpartum populations who screen positive for depression are needed to further understand the utility and efficacy of such digital therapeutics for that population.
围产期情绪障碍很常见,但诊断不足且未得到充分治疗或治疗不充分。获得围产期心理健康服务存在障碍,包括可及性有限、时间和成本问题。自动化对话代理(聊天机器人)可以通过基于文本消息的对话提供循证认知行为疗法内容,并减轻特定人群的抑郁和焦虑症状。此类数字心理健康技术有望克服获得心理健康护理的障碍,但需要评估其疗效以及在围产期人群中的初步可行性和可接受性。
评估一款心理健康聊天机器人在一般产后人群中进行情绪管理的可接受性和初步疗效。
在一家三级学术中心进行了一项非盲随机对照试验。年龄在18岁及以上、有活产且能使用智能手机的讲英语的产后妇女在分娩住院出院前有资格入组。在随机分配到心理健康聊天机器人干预组或仅接受常规护理组之前,对所有参与者进行基线调查。干预组除继续接受常规护理外,还下载了具有围产期特定内容的心理健康聊天机器人智能手机应用程序。常规护理包括由患者的产科医生规定的产后常规随访和心理健康护理。在分娩住院期间(基线)以及产后2周、4周和6周进行调查,以评估抑郁和焦虑症状。主要结局是使用两种抑郁筛查工具(患者健康问卷-9和爱丁堡产后抑郁量表)测量的产后6周时抑郁症状的变化。次要结局包括使用广泛性焦虑障碍-7测量的焦虑症状,以及使用经过验证的量表测量的满意度和可接受性。根据先前的一项研究,我们估计样本量为130将有足够的(80%)效力检测患者健康问卷-9组间差异中的中等效应量(d = 0.4)。
共有192名妇女按1:1比例随机分为聊天机器人组或常规护理组;其中,152名妇女完成了6周的调查(聊天机器人组n = 68,常规护理组n = 84)并纳入最终分析。平均基线心理健康评估分数低于阳性筛查阈值。在产后6周时,与常规护理组相比,聊天机器人组的患者健康问卷-9分数下降幅度更大(平均下降分别为1.32,标准差 = 3.4与平均下降0.13,标准差 = 3.01)。两组间产后6周的平均爱丁堡产后抑郁量表和广泛性焦虑障碍-7分数无差异,且与基线相似。91%(n = 62)的聊天机器人用户对聊天机器人感到满意或非常满意,74%(n = 50)的干预组报告在6周调查前的2周内至少使用过一次聊天机器人。80%的研究参与者报告对使用移动智能手机应用程序进行情绪管理感到满意。
产后早期妇女可接受使用聊天机器人。该样本在基线时未筛查出抑郁阳性,因此聊天机器人在该人群中减轻抑郁症状的潜力有限。本研究是在一般产科人群中进行的。需要对抑郁筛查呈阳性的高危产后人群进行更长时间的未来研究,以进一步了解此类数字疗法对该人群的效用和疗效。