Objective To obtain more precise and rich information from the measurements for schizotypal personality disorder (SPD), a cutting‐edge psychometric theory called diagnostic classification models (DCMs) was first employed in the present study to develop a diagnostic classification version of the Schizotypal Personality Questionnaire (DC‐SPQ) based on the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. Methods Under the framework of DCMs, 980 college students were recruited to calibrate item parameters of the Schizotypal Personality Questionnaire. Items that fit the psychometric characteristic would be selected to compose the DC‐SPQ, prior to an analysis of its indexes. Results Results showed that the DC‐SPQ had high reliability and validity in both the classical test theory and DCMs, in addition to showing a sensitivity of 0.921 and a specificity of 0.841 with area under receiver operating characteristic curve = 0.936. Meanwhile, the four‐factor model proposed adequately fits with the data. More importantly, the DC‐SPQ provides not only the general‐level information similar to traditional questionnaires but also the symptom‐level information with the posterior probability, which provides an insight into delivering the individual‐specific intervention that is tailor made to schizotypal personality disorder. Conclusions This study demonstrates that the DC‐SPQ is very valuable for psychometric detection in that it can clarify the symptom being measured and provide more reasonable estimates.

For various reasons, respondents to forced-choice assessments (typically used for noncognitive psychological constructs) may respond randomly to individual items due to indecision or globally due to disengagement. Thus, random responding is a complex source of measurement bias and threatens the reliability of forced-choice assessments, which are essential in high-stakes organizational testing scenarios, such as hiring decisions. The traditional measurement models rely heavily on nonrandom, construct-relevant responses to yield accurate parameter estimates. When survey data contain many random responses, fitting traditional models may deliver biased results, which could attenuate measurement reliability. This study presents a new forced-choice measure-based mixture item response theory model (called M-TCIR) for simultaneously modeling normal and random responses (distinguishing completely and incompletely random). The feasibility of the M-TCIR was investigated via two Monte Carlo simulation studies. In addition, one empirical dataset was analyzed to illustrate the applicability of the M-TCIR in practice. The results revealed that most model parameters were adequately recovered, and the M-TCIR was a viable alternative to model both aberrant and normal responses with high efficiency.

To obtain rich information about the cognitive diagnosis of borderline personality disorder (BPD), this study attempted to retrofit a traditional borderline personality questionnaire so that the improved assessment (called CDA-BPD) could provide more diagnostic information. The retrofitting processes included the following steps: (1) applied an cognitive diagnosis model to analyze the psychometric characteristics of the traditional questionnaire; (2) under the guidance of cognitive diagnosis assessment (CDA), high-quality items were chosen to develop the CDA-BPD and tested on 1,097 subjects; (3) the quality of the CDA-BPD was evaluated; (4) the structure of the CDA-BPD was analyzed. Results indicated that: (1) the CDA-BPD had acceptable reliability and validity; (2) the CDA-BPD had sensitivity of 0.985 and specificity of 0.853 with area under curve (AUC) = 0.956; (3) the two structural factors of the traditional questionnaire were confirmed in the CDA-BPD; χ2 was 83.01 with df = 26, p < .0001, comparative fit index (CFI) = 0.97, root mean square error of approximation (RMSEA) = 0.045. It was concluded that the practice of retrofitting a traditional borderline personality assessment for cognitive diagnostic purpose was feasible. Most importantly, under the cognitive diagnosis model framework, CDA-BPD could simultaneously provide general-level information and the detailed symptom criteria-level information about the posterior probability of satisfying each symptom criterion in the Diagnostic and Statistical Manual of Mental Disorders (5th edition; DSM-5; American Psychiatric Association, 2013) for each individual, which gave further insight into tailoring individual-specific treatments for borderline personality disorder.

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