Abstract

OBJECTIVE: Examine which participant level factors impact the time to switch from first- to second-generation agents among participants in the Schizophrenia Care and Assessment Project (SCAP). METHODS: Baseline data identified participants not receiving second generation agents (n = 520). Accelerated failure time (AFT) modeling (Weibull distribution error) applied. Number of years between disease onset and study initiation included. Dependent variable: days between study initiation and first switch to second-generation. Right censoring addressed through dichotomous censor variable (1 = switch during window). RESULTS: About one-fourth (n = 133) experienced switch (mean time to switch = 171.08 days). Working hypothesis: persons with higher side effect and symptom scores and lower functioning would exhibit shorter time to switch. Persons with higher side effect scores (AIMS) experienced longer interval until switch (1.08; p = 0.01) and those with higher depression scores (MADRS) experienced shorter time to switch (0.97; p = 0.02). Those receiving service through university hospital experienced longer interval (3.19; p = 0.01). The computed hazard rate (−0.68) indicates the risk of switch is decreasing over time. CONCLUSIONS: Findings indicate that symptoms and type of service delivery site are significant in determining the switch from older to newer agents. The shorter interval for those with higher depression scores is expected and is probably reflective of clinical intervention aimed toward the amelioration of negative symptoms. Interestingly, the longer interval for those with higher side effect scores was contrary to expectation and may indicate that the motivating influence to change is more related to the presentation of primary disease state, rather than the reduction of secondary symptoms associated with the first generation medications. The longer interval for those receiving care in a university hospital setting is perplexing since it is usually expected that medication adjustment will occur during hospital stays. Further investigation of this phenomenon may be aided by the inclusion of physician level information, which is anticipated in upcoming analyses.

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