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Background: Serious mental illness (SMI) is profoundly stigmatised, such that there is even an impact on relatives of people with SMI. Aims To develop and validate a scale to comprehensively measure self-stigma among first-degree relatives of individuals with SMI.Method: We conducted group interviews focusing on self-stigma with first-degree relatives (n = 20) of people with SMI, from which 74 representative quotations were reframed as Likert-type items. Cognitive interviews with relatives (n = 11) identified 30 items for the Self-Stigma in Relatives of people with Mental Illness (SSRMI) scale. Relatives (n = 195) completed the scale twice, a month apart, together with four external correlate scales.Results: The 30-item SSRMI was reliable, with scores stable over time. Its single-factor structure allowed generation of a 10-item version. Construct validity of 30- and 10-item versions was supported by expected relationships with external correlates.Conclusions: Both versions of the SSRMI scale are valid and reliable instruments appropriate for use in clinical and research contexts. Declaration of interest None. [ABSTRACT FROM AUTHOR]

State estimation is difficult when the system has multiple modes of operation. Modal transitions create discontinuities in the reference point for the local state variables. The uncertain reference point increases the ambiguity in the state measurement. The paper presents an estimation algorithm that can be used in multimodal applications. The algorithm is shown to be superior to the Kalman filter when the state measurement is contaminated with a mode dependent offset. Despite the uncertain reference point in the observation, good estimates of the underlying entire state processes can be generated [ABSTRACT FROM PUBLISHER]