Mackenzie P E Becker1, Bruce K Christensen1, Charles E Cunningham1, Ivana Furimsky1, Heather Rimas1, Fiona Wilson1, Lisa Jeffs1, Peter J Bieling1, Victoria Madsen1, Yvonne Y S Chen1, Stephanie Mielko1, Robert B Zipursky1. 1. Ms. Becker is with the Department of Psychology, Neuroscience and Behaviour, and Dr. Cunningham, Ms. Furimsky, Ms. Rimas, Ms. Wilson, Dr. Bieling, Ms. Chen, Ms. Mielko, and Dr. Zipursky are with the Department of Psychiatry and Behavioural Neurosciences, all at McMaster University, Hamilton, Ontario, Canada. Ms. Furimsky, Ms. Wilson, Dr. Bieling, and Dr. Zipursky are also with the Mental Health and Addiction Program, St. Joseph's Healthcare Hamilton, Hamilton, Ontario, where Ms. Jeffs and Ms. Madsen are affiliated. Dr. Cunningham is also with the Department of Psychiatry, McMaster Children's Hospital, Hamilton, Ontario. Ms. Chen is also with the School of Business, University of Alberta, Edmonton, Alberta. Dr. Christensen is with the Research School of Psychology, Australian National University, Canberra, Australia. Send correspondence to Dr. Zipursky (e-mail: zipursky@mcmaster.ca ).
Abstract
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.
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.
Authors: Loes Hilhorst; Jip van der Stappen; Joran Lokkerbol; Mickaël Hiligsmann; Anna H Risseeuw; Bea G Tiemens Journal: Adm Policy Ment Health Date: 2022-04-15