Preferences for Early Intervention Mental Health Services: A Discrete-Choice Conjoint Experiment
Preferences for Early Intervention Mental Health Services: A Discrete-Choice Conjoint Experiment
复制标题
DOI：
10.1176/appi.ps.201400306
复制
发表时间：
2016-02-01
影响因子：
3.8
通讯作者：
Zipursky, Robert B.
中科院分区：
文献类型：
--
作者：
Becker, Mackenzie P. E.;Christensen, Bruce K.;Zipursky, Robert B.
目的：精神疾病的早期干预服务（EIS）可能会改善结果，尽管治疗参与往往是一个问题。在干预措施的设计中考虑患者的偏好可以提高参与度。一个离散的选择联合实验在加拿大进行，以确定EIS属性，鼓励treatmentinitiation.Methods：16个四级属性被正式纳入联合调查，完成由患者，家属和精神卫生专业人员（N=562）。参与者被问到精神疾病患者会联系哪种EIS选项。潜在的类分析确定受访者类的共同喜好。随机第一选择模拟预测的假设选项，属性的基础上，将导致最大utilization.Results：参与者在传统的服务类（N=241，43%）预测，个人会接触传统的服务（例如，医院的位置和工作人员由心理学家或精神科医生）。成员资格与患者或家庭成员以及男性有关。参与者在咨询服务类（N=321，57%）预测，人们会接触服务，促进容易获得（例如，自我转诊和从家里访问）。会员资格与专业人士有关。这两个类别都预测人们会接触包括短等待时间，与专业人员直接接触，患者自主权和心理治疗信息在内的服务。预测，人们将使用电子健康模型，而传统的服务类预测，人们将使用初级保健或诊所医院model.Conclusions：提供一系列的服务，可以最大限度地利用EIS。专业人士可能更倾向于采用符合他们的信念，病人的喜好。考虑几个方面对于服务设计很重要。
Objective: Early intervention services (EISs) for mental illness may improve outcomes, although treatment engagement is often a problem. Incorporating patients' preferences in the design of interventions improves engagement. A discrete-choice conjoint experiment was conducted in Canada to identify EIS attributes that encourage treatment initiation.Methods: Sixteen four-level attributes were formalized into a conjoint survey, completed by patients, family members, and mental health professionals (N=562). Participants were asked which EIS option people with mental illness would contact. Latent-class analysis identified respondent classes characterized by shared preferences. Randomized first-choice simulations predicted which hypothetical options, based on attributes, would result in maximum utilization.Results: Participants in the conventional-service class (N=241, 43%) predicted that individuals would contact traditional services (for example, hospital location and staffed by psychologists or psychiatrists). Membership was associated with being a patient or family member and being male. Participants in the convenient-service class (N=321, 57%) predicted that people would contact services promoting easy access (for example, self-referral and access from home). Membership was associated with being a professional. Both classes predicted that people would contact services that included short wait times, direct contact with professionals, patient autonomy, and psychological treatment information. The convenient-service class predicted that people would use an e-health model, whereas the conventional-service class predicted that people would use a primary care or clinic-hospital model.Conclusions: Provision of a range of services may maximize EIS use. Professionals may be more apt to adopt EISs in line with their beliefs regarding patient preferences. Considering several perspectives is important for service design.