Comparing Clinical Decision-making of AI Technology to a Multi-professional Care Team in an Electronic Cognitive Behavioural Therapy Program for Depression
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 186
- 试验地点
- 2
- 主要终点
- Change in Assessment of Quality of Life (AQoL-8D) Score
研究概览
简要总结
Depression is a leading cause of disability worldwide, affecting up to 300 million people globally. Despite its high prevalence and debilitating effects, only one-third of patients newly diagnosed with depression initiate treatment. Electronic cognitive behavioural therapy (e-CBT) is an effective treatment for depression and is a feasible solution to make mental health care more accessible. Due to its online format, e-CBT can be combined with variable therapist engagement to address different care needs. Typically, a multi-professional care team determines which combination therapy is the most beneficial to the patient. However, this process can add to the costs of these programs. Artificial intelligence (AI) technology has been proposed to offset these costs. Therefore, this study aims to determine a cost-effective method to decrease depressive symptoms and increase treatment adherence to e-CBT. This will be done by comparing AI technology to a multi-professional care team when allocating the correct intensity of care for individuals diagnosed with depression. This study is a double-blinded randomized controlled trial recruiting individuals (n = 186) experiencing depression according to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5). The degree of care intensity a participant will receive will be randomly decided by either: (1) a machine learning algorithm (n = 93), or (2) an assessment made by a group of healthcare professionals (n = 93). Subsequently, participants will receive depression-specific e-CBT treatment through the secure online platform, OPTT. There will be three available intensities of therapist interaction: (1) e-CBT; (2) e-CBT with a 15-20-minute phone/video call; and (3) e-CBT with pharmacotherapy. This approach aims to accurately allocate care tailored to each patient's needs, allowing for more efficient use of resources.
详细描述
Participants (n = 186: n = 31 per e-CBT group * 2 arms) will be recruited at Queen's University from outpatient psychiatry clinics at both Kingston Health Sciences Centre sites (Hotel Dieu Hospital and Kingston General Hospital), as well as Providence Care Hospital in Kingston, Ontario. Additionally, self-referrals and referrals from family doctors, physicians, and clinicians across Ontario will be accepted. After obtaining informed consent from the participant, the participant will be evaluated using the Mini International Psychiatric Assessment (MINI) through a secure video appointment to confirm a diagnosis of Major Depressive Disorder using the DSM-5 by a trained professional on the research team.
All eligible participants will be randomized to receive a treatment plan based on the decision of either the healthcare team (Arm 1) or the Triage Module using an AI algorithm (Arm 2). Participants will be randomly allocated to one of the two arms of the study by a research assistant on the team who will also balance the group based on demographic variables (i.e., sex, gender, age, and income). Participants and therapists in the study will be blinded to which treatment arm the participant belongs to. By the nature of this study, participants and therapists will not be blinded to which treatment intensity the participant will receive since it will be evident whether the participant is receiving a phone/video call in addition to usual e-CBT care or pharmacotherapy. Each participant will be provided with an effective form of treatment (i.e., e-CBT) regardless of which group they will be allocated to. Participants will be informed that there is no incentive for joining the program and that joining or withdrawing at any point will not affect them negatively. It will also be explained to the participants that the program is not a crisis resource and that they will not always have access to their therapists. In the case of an emergency, participants will be directed to proper resources, and this event will be reported to the study's lead psychiatrist (principal investigator). All data will be anonymized and will be analyzed by members of the research team who are not directly involved in the patient's care.
Treatment Arm 1: Healthcare Team Allocation
Allocation of treatment intensity by the multi-professional healthcare team will be based on the following criteria:
- The severity of MDD symptoms (using DSM-5 criteria).
- Mental health factors (prior treatments and responses, current and past psychotic/manic episodes, current and past suicidal/homicidal ideation/attempts, family mental health history, past psychiatric history, and hospital admissions).
- Medical factors (current medical conditions and medications, personal and family medical history).
- Social factors (support system and living situation, and occupational, social, and personal functional impairment).
研究设计
- 研究类型
- Interventional
- 分配方式
- Randomized
- 干预模型
- Parallel
- 主要目的
- Treatment
- 盲法
- Double (Care Provider, Investigator)
盲法说明
To ensure blinding, all participants will complete the intake assessment by the healthcare team (Arm 1) and the Triage Module (Arm 2). Only the relevant data (i.e., Arm 1: intake assessment vs. Arm 2: Triage Module) will be analyzed depending on the treatment arm that the participant is randomly assigned to.
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Diagnosed with MDD by a trained research assistant according to the criteria outlined in the DSM-5
- •Ability to provide informed consent
- •Ability to speak and read English
- •Having consistent and reliable access to the internet
排除标准
- •Active psychosis
- •Acute mania
- •Severe alcohol, or substance use disorder
- •Active suicidal or homicidal ideation
- •Currently receiving psychotherapy
结局指标
主要结局
Change in Assessment of Quality of Life (AQoL-8D) Score
时间窗: week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.
Scale of 0-5 per question, 0 = better, 5 = worse
Change in Quick Inventory of Depressive Symptoms (QIDS) Score
时间窗: week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.
Scale of 0-3 per question, 0 = better, 3 = worse
Change in Patient Health Questionnaire (PHQ-9) Score
时间窗: week 0, 4, 7, 10, 13, and 3, 6, and 12-month follow-up.
Scale of 0-3 per question, 0 = not at all, 3 = nearly every day, higher score = worse
次要结局
未报告次要终点
研究者
Dr. Nazanin Alavi
Assistant Professor
Queen's University
