Development and Preliminary Validation of the Scale for Evaluation of Psychiatric Integrative and Continuous...

This pilot study aimed to evaluate and examine an instrument that integrates relevant aspects of cross-sectoral (in- and outpatients) mental health care, is simply to use and shows satisfactory psychometric properties. The development of the scale comprised literature research, held 14 focus groups and 12 interviews with patients and health care providers, item-pool generation, content validation by a scientific expert panel, and face validation by 90 patients. The preliminary scale was tested on 385 patients across seven German hospitals with cross-sectoral mental health care (CSMHC) as part of their treatment program. Psychometric properties of the scale were evaluated using genuine and transformed data scoring. To check reliability and postdictive validity of the scale, Cronbach's α coefficient and multivariable linear regression were used. This development process led to the development of an 18-item scale called the "Scale for Evaluation of Psychiatric Integrative and Continuous Care (SEPICC)" with a two-point and five-point response options. The scale consists of two sections. The first section assesses the presence or absence of patients' experiences with various CSMHC' relevant components such as home treatment, flexibility of treatments' switching, case management, continuity of care, cross-sectoral therapeutic groups, and multidisciplinary teams. The second section evaluates the patients' opinions about these relevant components. Using raw and transformed scoring resulted into comparable results. However, data distribution using transformed scoring showed a smaller deviation from normality. For the overall scale, the Cronbach's α coefficient was 0.82. Self-reported experiences with relevant components of the CSMHC were positively associated with the patients approval of these components. In conclusion, the new scale provides a good starting point for further validation. It can be used as a tool to evaluate CSMHC. Methodologically, using transformed data scoring appeared to be preferable because of a smaller deviation from normality and a higher reliability measured by Cronbach's α.