An observer-rated strategy for differentiating schizophrenic and manic states in inpatient settings

Objectives: Differentiating schizophrenia from mania in acutely psychotic patients can be difficult, but is important in determining immediate and subsequent management. Such differentiation is generally addressed by clinical interviews, but an observational approach may assist. This paper therefore describes the development of a relevant observational measure. Methods: We developed a provisional list of 49 items (weighting features with suggested specificity to schizophrenia and mania) for independent completion by two nurses and judged its ability to predict diagnosis provided by consultant psychiatrists. Results: Eighty-seven psychotic patients were recruited, and 173 completed data sets were analysed. We refined the item set to two sets of 10 items that best-differentiated schizophrenia from mania and vice versa. Optimal differentiation was achieved with a score of at least 7 on both the schizophrenia and mania item sets. Difference scores (i.e. schizophrenia items affirmed minus mania items affirmed) were also generated, with a difference score of +1 (i.e. one or more schizophrenia items being affirmed than mania items) showing optimal differentiation (sensitivity 0.67, specificity 0.82) between the two conditions. Evaluating all potential difference scores, we demonstrated that, as difference scores increased, diagnostic accuracy in identifying each condition was very high. Conclusion: Analyses allow the properties of an observational measure (the 20-item Sydney Psychosis Observation Tool) to be described. While a single cut-off difference score was derived with acceptable discriminatory ability, we also established the capacity of varying difference scores to assign both schizophrenia and mania diagnoses with high accuracy.

• Publication year

  2023

• Venue

  Australian and New Zealand journal of psychiatry (Print)

• Publication date

  2023-09-28

• Fields of study

  Medicine, Psychology

• Identifiers
  DOI 10.1177/00048674231201545PMID 37771099PMCID 10756020
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar, PubMed

• No claims are published for this paper.

• No concepts are published for this paper.

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