Goodsmith Nichole, Cohen Amy N, Flynn Anthony W P, Hamilton Alison B, Hellemann Gerhard, Nowlin-Finch Nancy, Young Alexander S
Department of Veterans Affairs (VA) Center for the Study of Healthcare Innovation, Implementation, and Policy, Health Services Research and Development Service, VA Greater Los Angeles Healthcare System, Los Angeles (Goodsmith, Hamilton); National Clinician Scholars Program, University of California, Los Angeles (UCLA), Los Angeles (Goodsmith); VA Desert Pacific Mental Illness Research, Education, and Clinical Center, Los Angeles (Goodsmith, Young); American Psychiatric Association (Cohen); Department of Counseling Psychology, University of Wisconsin-Madison, Madison (Flynn); Department of Psychiatry and Biobehavioral Sciences, UCLA, Los Angeles (Hamilton, Hellemann, Nowlin-Finch, Young); Los Angeles County Department of Mental Health, Los Angeles (Nowlin-Finch).
Psychiatr Serv. 2021 Mar 1;72(3):288-294. doi: 10.1176/appi.ps.202000068. Epub 2021 Jan 12.
Innovative approaches are needed for assessing treatment preferences of individuals with schizophrenia. Conjoint analysis methods may help to identify preferences, but the usability and validity of these methods for individuals with schizophrenia remain unclear. This study examined computerized conjoint analysis for persons with schizophrenia and whether preferences for weight management programs predict service use.
A computerized, patient-facing conjoint analysis system was developed through iterative consultation with 35 individuals with schizophrenia enrolled at a community mental health clinic. An additional 35 overweight participants with schizophrenia then used the system to choose among psychosocial weight management programs varying in four attributes: location (community or clinic), delivery mode (Internet or in person), leader (clinician or layperson), and training mode (individual or group). A multilevel logit model with partial preference data determined contributions of each attribute to groupwide preferences. Associations were studied between preferences and use of a psychosocial weight management group.
Conjoint analysis system usability was rated highly. Groupwide preferences were significantly influenced by location (p<0.001; clinic was preferred), leader (p=0.02; clinician was preferred), and training mode (p<0.001; group was preferred) but not delivery mode (p=0.68). Preferences did not correlate with age, gender, body mass index, illness severity, or subsequent program use. Participants described barriers to program attendance, including transportation, scheduling, privacy, psychiatric illness, and lack of motivation.
Computerized conjoint analysis can produce valid assessments of treatment preferences of persons with schizophrenia and inform treatment development and implementation. Although preferences may affect treatment use, they are one of multiple factors.
需要创新方法来评估精神分裂症患者的治疗偏好。联合分析方法可能有助于识别偏好，但这些方法对精神分裂症患者的可用性和有效性仍不明确。本研究考察了针对精神分裂症患者的计算机化联合分析，以及体重管理项目的偏好是否能预测服务利用情况。
通过与一家社区心理健康诊所登记的35名精神分裂症患者进行反复咨询，开发了一个面向患者的计算机化联合分析系统。另外35名超重的精神分裂症参与者随后使用该系统在四个属性不同的心理社会体重管理项目中进行选择：地点（社区或诊所）、提供方式（互联网或面对面）、领导者（临床医生或外行人）和培训方式（个体或团体）。一个具有部分偏好数据的多级逻辑模型确定了每个属性对全组偏好的贡献。研究了偏好与心理社会体重管理组的使用之间的关联。
联合分析系统的可用性得到高度评价。全组偏好受到地点（p<0.001；更喜欢诊所）、领导者（p=0.02；更喜欢临床医生）和培训方式（p<0.001；更喜欢团体）的显著影响，但不受提供方式的影响（p=0.68）。偏好与年龄、性别、体重指数、疾病严重程度或随后的项目使用无关。参与者描述了参加项目的障碍，包括交通、日程安排、隐私、精神疾病和缺乏动力。
计算机化联合分析可以对精神分裂症患者的治疗偏好进行有效的评估，并为治疗的开发和实施提供信息。尽管偏好可能会影响治疗的使用，但它们只是多个因素之一。
