Computerized Conjoint Analysis of the Weight Treatment Preferences of Individuals With Schizophrenia

Nichole Goodsmith; Amy N Cohen; Anthony W P Flynn; Alison B Hamilton; Gerhard Hellemann; Nancy Nowlin-Finch; Alexander S Young

doi:10.1176/appi.ps.202000068

Computerized Conjoint Analysis of the Weight Treatment Preferences of Individuals With Schizophrenia

Psychiatr Serv. 2021 Mar 1;72(3):288-294. doi: 10.1176/appi.ps.202000068. Epub 2021 Jan 12.

Authors

Nichole Goodsmith¹, Amy N Cohen¹, Anthony W P Flynn¹, Alison B Hamilton¹, Gerhard Hellemann¹, Nancy Nowlin-Finch¹, Alexander S Young¹

Affiliation

¹ 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).

Abstract

Objective: 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.

Methods: 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.

Results: 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.

Conclusions: 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.

Keywords: Conjoint analysis; Health informatics; Mental illness; Patient preferences; Schizophrenia; Weight management.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Ambulatory Care Facilities
Humans
Patient Preference
Schizophrenia* / therapy

Grants and funding

R21 MH100565/MH/NIMH NIH HHS/United States