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. 2022 Oct:316:114773.
doi: 10.1016/j.psychres.2022.114773. Epub 2022 Aug 6.

Symptom monitoring based on digital data collection during inpatient treatment of schizophrenia spectrum disorders - A feasibility study

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Symptom monitoring based on digital data collection during inpatient treatment of schizophrenia spectrum disorders - A feasibility study

Julian Herpertz et al. Psychiatry Res. 2022 Oct.

Abstract

Digital acquisition of patients' self-reports on individual risk factors and symptom severity represents a promising, cost-efficient, and increasingly prevalent approach for standardized data collection in psychiatric clinical routine. Yet, studies investigating digital data collection in patients with a schizophrenia spectrum disorder (PSSDs) are scarce. The objective of this study was to explore the feasibility of digitally acquired self-report assessments of risk and symptom profiles at the time of admission into inpatient treatment in an age-representative sample of hospitalized PSSDs. We investigated the required support, the data entry pace, and the subjective user experience. Findings were compared with those of patients with an affective disorder (PADs). Of 82 PSSDs who were eligible for inclusion, 59.8% (n=49) agreed to participate in the study, of whom 54.2% (n=26) could enter data without any assistance. Inclusion rates, drop-out rates, and subjective experience ratings did not differ between PSSDs and PADs. Patients reported high satisfaction with the assessment. PSSDs required more support and time for the data entry than PADs. Our results indicate that digital data collection is a feasible and well-received method in PSSDs. Future clinical and research efforts on digitized assessments in psychiatry should include PSSDs and offer support to reduce digital exclusion.

Keywords: Digital assessment; Electronic health record; Patient-reported outcome; Psychiatry; Psychosis; Risk and symptom profiles.

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Conflict of interest statement

Conflict of Interest The authors have no conflicts of interest to declare that are relevant to the content of this article.

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