Show me you care: A patient‐ and family‐reported measure of care experiences in early psychosis services

330 Psychometrics 610 Reproducibility of Results India 3. Good health 03 medical and health sciences 0302 clinical medicine Psychotic Disorders Surveys and Questionnaires Early Intervention, Educational Humans Language
DOI: 10.1111/eip.13360 Publication Date: 2022-10-06T08:27:13Z
ABSTRACT
AbstractAimDespite their emphasis on engagement, there has been little research on patients' and families' experiences of care in early intervention services for psychosis. We sought to compare patients' and families' experiences of care in two similar early psychosis services in Montreal, Canada and Chennai, India. Because no patient‐ or family‐reported experience measures had been used in a low‐ and middle‐income context, we created a new measure, Show me you care. Here we present its development and psychometric properties.MethodsShow me you care was created based on the literature and stakeholder inputs. Its patient and family versions contain the same nine items (rated on a 7‐point scale) about various supportive behaviours of treatment providers towards patients and families. Patients (N = 293) and families (N = 237) completed the measure in French/English in Montreal and Tamil/English in Chennai. Test–retest reliability, internal consistency, convergent validity, and ease of use were evaluated.ResultsTest–retest reliability (intra‐class correlation coefficients) ranged from excellent (0.95) to good (0.66) across the patient and family versions, in Montreal and Chennai, and in English, French, and Tamil. Internal consistency estimates (Cronbach's alphas) were excellent (≥0.87). The measure was reported to be easy to understand and complete.ConclusionShow me you care fills a gap between principles and practice by making engagement and collaboration as central to measurement in early intervention as it is to its philosophy. Having been co‐designed and developed in three languages and tested in a low‐and‐middle‐income and a high‐income context, our tool has the potential for global application.
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