Preoccupation and distress are relevant dimensions in delusional beliefs.

BACKGROUND AND PURPOSE: A large number of subjective experiences and beliefs with some degree of affinity with psychotic symptoms can be found in the general population. However, the appraisal of these psychotic-like experiences in terms of associated distress, raised preoccupation, and the conviction with which the experience is held can be more discriminative in distinguishing people in need for care from those who simply hold unusual or uncommon beliefs because of cultural reasons. METHOD: In this study, 81 patients with a Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, diagnosis of schizophrenia or an affective disorder with psychotic features were compared on the Peters et al Delusions Inventory (PDI) to 210 people from the same local area, who had never received a formal diagnosis of a mental disorder. RESULTS: Patients scored higher than controls on the PDI total score and on its distress, preoccupation, and conviction subscales. A stepwise logistic regression model showed PDI-preoccupation (odds ratio, 2.46; 95% confidence interval, 1.52-3.98) and, marginally, PDI-distress (odds ratio = 1.58; 95% confidence interval, 0.93-2.58) adding discriminative power to PDI total score in distinguishing patients from controls. CONCLUSIONS: The evaluation of the severity of delusion-like experiences and beliefs is important in discriminating patients diagnosed with psychosis from people who are not in need of care.

Latent class analysis of delusion-proneness: exploring the latent structure of the Peters et al. delusions inventory.

Latent class analysis (LCA) has emerged as the best suitable statistical tool to identify separate dimensions (latent classes) when analyzing dichotomous data; its objective is to categorize people into classes using the observed items and to identify those items that best distinguish between classes. LCA was applied to the Peters et al. delusions inventory, an inventory in a dichotomous format (Yes/No) aimed at investigating proneness to delusion in the general population. The study involved 82 patients diagnosed with a psychotic disorder and 210 well-matched healthy controls from the community. Four classes were identified in the sample: a normative one, and 3 classes traceable to the 3 major dimensions of psychosis, i.e., paranoia, grandiosity/hypomania, and the schizophrenia-like profile. The coherent multidimensional structure of the model emerging from LCA of Peters et al. delusions inventory suggests that single clusters of symptoms may be indicative of specific diagnostic categories within the spectrum of psychoses, allowing a more subtle determination of their boundaries and correlates.

The psychometric discriminative properties of the Peters et al Delusions Inventory: a receiver operating characteristic curve analysis.

OBJECTIVE: To establish sensitivity, specificity, and discriminative validity of the Peters et al Delusions Inventory (PDI), a recently released self-compiled questionnaire aimed at measuring psychosis proneness in the general population. METHOD: Eighty-one patients diagnosed with a mental disorder with psychotic features (schizophrenia, schizoaffective disorder, bipolar disorder, major depression) and 210 putatively healthy individuals were invited to complete the PDI and the brief version of the General Health Questionnaire (GHQ-12). The receiver operating characteristic analysis has been used to extract the best threshold to discriminate between cases, those with a psychotic disorder, and noncases, those without a psychotic disorder. RESULTS: The best PDI threshold in discriminating between cases and noncases was 8 (sensitivity, 74%; specificity, 79%). The corresponding figures of sensitivity and specificity for a GHQ-12 cutoff of 6 were 63% and 83%, respectively. The value of the area under the receiver operating characteristic curve was found to be higher for the PDI (0.815) than for the GHQ-12 (0.770), although at a barely detectable, statistically significant difference (Z = 1.45, P = .073). CONCLUSION: The expected high negative predictive value of the PDI (96%) in the general population suggests it will be a valuable tool in future research on psychosis proneness.