Investigating service features to sustain engagement in early intervention mental health services.

AIM: To understand what service features would sustain patient engagement in early intervention mental health treatment. METHODS: Mental health patients, family members of individuals with mental illness and mental health professionals completed a survey consisting of 18 choice tasks that involved 14 different service attributes. Preferences were ascertained using importance and utility scores. Latent class analysis revealed segments characterized by distinct preferences. Simulations were carried out to estimate utilization of hypothetical clinical services. RESULTS: Overall, 333 patients and family members and 183 professionals (N = 516) participated. Respondents were distributed between a Professional segment (53%) and a Patient segment (47%) that differed in a number of their preferences including for appointment times, individual vs group sessions and mode of after-hours support. Members of both segments shared preferences for many of the service attributes including having crisis support available 24 h per day, having a choice of different treatment modalities, being offered help for substance use problems and having a focus on improving symptoms rather than functioning. Simulations predicted that 60% of the Patient segment thought patients would remain engaged with a Hospital service, while 69% of the Professional segment thought patients would be most likely to remain engaged with an E-Health service. CONCLUSIONS: Patients, family members and professionals shared a number of preferences about what service characteristics will optimize patient engagement in early intervention services but diverged on others. Providing effective crisis support as well as a range of treatment options should be prioritized in the future design of early intervention services.

Preferences for Early Intervention Mental Health Services: A Discrete-Choice Conjoint Experiment.

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.