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Questionnaires inquiring about psychopathology symptoms often produce data with excess zeros or the equivalent (e.g., none, never, and not at all). This type of zero inflation is especially common in nonclinical samples in which many people do not exhibit psychopathology, and if unaccounted for, can result in biased parameter estimates when fitting latent variable models. In the present research, we adopt a maximum likelihood approach in fitting multidimensional zero-inflated and hurdle graded response models to data from a psychological distress measure. These models include two latent variables: susceptibility, which relates to the probability of endorsing the symptom at all, and severity, which relates to the frequency of the symptom, given its presence. After estimating model parameters, we compute susceptibility and severity scale scores and include them as explanatory variables in modeling health-related criterion measures (e.g., suicide attempts, diagnosis of major depressive disorder). Results indicate that susceptibility and severity uniquely and differentially predict other health outcomes, which suggests that symptom presence and symptom severity are unique indicators of psychopathology and both may be clinically useful. Psychometric and clinical implications are discussed, including scale score reliability.

Objective: Despite the public health burden of traumatic brain injury (TBI) across broader society, most TBI studies have been isolated to a distinct subpopulation. The TBI research literature is fragmented further because often studies of distinct populations have used different assessment procedures and instruments. Addressing calls to harmonize the literature will require tools to link data collected from different instruments that measure the same construct, such as civilian mild traumatic brain injury (mTBI) and sports concussion symptom inventories. Method: We used item response theory (IRT) to link scores from the Rivermead Post Concussion Symptoms Questionnaire (RPQ) and the Sport Concussion Assessment Tool (SCAT) symptom checklist, widely used instruments for assessing civilian and sport-related mTBI symptoms, respectively. The sample included data from n = 397 patients who suffered a sports-related concussion, civilian mTBI, orthopedic injury control, or non-athlete control and completed the SCAT and/or RPQ. Results: The results of several analyses supported sufficient unidimensionality to treat the RPQ + SCAT combined item set as measuring a single construct. Fixed-parameter IRT was used to create a cross-walk table that maps RPQ total scores to SCAT symptom severity scores. Linked and observed scores were highly correlated (r = .92). Standard errors of the IRT scores were slightly higher for civilian mTBI patients and orthopedic controls, particularly for RPQ scores linked from the SCAT. Conclusion: By linking the RPQ to the SCAT we facilitated efforts to effectively combine samples and harmonize data relating to mTBI.

The Glasgow Outcome Scale-Extended (GOSE) is a functional outcome measure intended to place individuals with traumatic brain injury (TBI) into one of eight broad levels of injury-related disability. This simplicity is not always optimal, particularly when more granular assessment of individuals’ injury recovery is desired. The GOSE, however, is customarily assessed using a multi-question interview that contains richer information than is reflected in the GOSE score. Using data from the multi-center Transforming Research and Clinical Knowledge in TBI (TRACK-TBI) study (N = 1544), we used item response theory (IRT) to evaluate whether rescoring the GOSE using IRT, which posits that a continuous latent variable (disability) underlies responses, can yield a more precise index of injury-related functional limitations. We fit IRT models to GOSE interview responses collected at three months post-injury. Each participant's level of functional limitation was estimated from the model (GOSE-IRT) and comparisons were made between IRT-based and standard (GOSE-Ordinal) scores. The IRT scoring resulted in 141 possible scores (vs. 7 GOSE-Ordinal scores in this sample of individuals with GOSE scores ranging between 2 and 8). Moreover, GOSE-IRT scores were significantly more strongly associated with measures of TBI-related symptoms, psychological symptoms, and quality of life. Our findings demonstrate that rescoring the GOSE interview using IRT yields more granular, meaningful measurement of injury-related functional limitations, while adding no additional respondent or examiner burden. This technique may have utility for many applications, such as clinical trials aiming to detect small treatment effects, and small-scale studies that need to maximize statistical efficiency.

Clinical instruments that use a filter/follow-up response format often produce data with excess zeros, especially when administered to nonclinical samples. When the unidimensional graded response model (GRM) is then fit to these data, parameter estimates and scale scores tend to suggest that the instrument measures individual differences only among individuals with severe levels of the psychopathology. In such scenarios, alternative item response models that explicitly account for excess zeros may be more appropriate. The multivariate hurdle graded response model (MH-GRM), which has been previously proposed for handling zero-inflated questionnaire data, includes two latent variables: susceptibility, which underlies responses to the filter question, and severity, which underlies responses to the follow-up question. Using both simulated and empirical data, the current research shows that compared to unidimensional GRMs, the MH-GRM is better able to capture individual differences across a wider range of psychopathology, and that when unidimensional GRMs are fit to data from questionnaires that include filter questions, individual differences at the lower end of the severity continuum largely go unmeasured. Practical implications are discussed.

A limited evidence base supports the Functional Status Examination (FSE) as superior to the more commonly used Glasgow Outcome Scale–Extended (GOSE) for precisely characterizing injury-related functional limitations. The aim of this study was to use modern psychometric tools to test the hypothesis that the FSE is more precise than the GOSE in characterizing individual differences in functional limitations after moderate-to-severe traumatic brain injury (TBI). Secondarily, we sought to confirm that the type of interviewee (patient, significant other) does not affect the test performance of the FSE. Using data from 357 individuals with TBI who participated in the Magnesium Sulfate clinical trial and had six-month outcome data, we performed item response theory (IRT) analyses comparing the FSE and GOSE at six months post-injury. Results showed that the FSE yielded higher measurement precision (IRT test information) than the GOSE across most of the disability severity spectrum. The GOSE yielded more information than the FSE at a very high level of disability, because of the GOSE's assignment of a unique score for individuals who are in a vegetative state. Finally, the FSE showed no evidence of differential item functioning by interviewee, indicating it is appropriate to interview either persons with TBI or significant others and combine data across respondents as is typically done. The findings support the FSE as a viable and oftentimes advantageous substitute for the GOSE in clinical trials and translational studies of TBI.

Zero responses and their equivalents-for example, never, none, not at all-are commonly observed on measures of psychopathology inquiring about symptom frequencies, particularly when these measures are administered to community samples. Measurement researchers typically accommodate multivariate zero inflation by including a nonpathological class of respondents who endorse zero for all symptoms. While this latent class approach accounts for test-level zero inflation (i.e., a proportion of individuals who do not experience any of the symptoms), it may be overly restrictive on questionnaires comprising items of differing severity. For example, an item about suicidal ideation is likely to exhibit a much higher degree of zero inflation than an item about low energy. Existing models do not account for this variability. We propose a multidimensional zero-inflated graded response model (MZI-GRM) as a more flexible approach for modeling zero inflation on questionnaires. According to the model, two distinct but correlated latent variables underlie ordinal item responses; one represents susceptibility to the construct, whereas the other represents severity. As a motivating example, we show how the MZI-GRM can be fit to data from the PHQ-9, a common depression screener. Results suggest that the MZI-GRM is better able to capture zero inflation across items than existing alternative models. Further, we find support for a multidimensional model that allows distinct but correlated latent variables to underlie each response process. Some items better measure susceptibility to depression (symptom presence), whereas others better capture severity of depression (symptom frequency). Implications for scale development and scoring are discussed. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The presence–severity response format uses a filter question to ask about the presence of a symptom, followed by a question about the severity of that symptom. Only an affirmative response to the filter question triggers the follow-up question. Despite its widespread use, little research has compared the psychometric properties of the presence–severity response format to those of the traditional single-item response format. The purpose of this research was to understand how filter questions influence item responses and characteristics on several short health-related questionnaires. Using two different experimental designs, we find that depending on the construct being measured, the inclusion of a filter question can have a substantial effect on people’s responses, and in turn, the psychometric properties of the items. Overall, the presence–severity response format results in a reduction in symptom reporting and loss of information about individual differences, particularly for people experiencing mild symptoms. Measurement recommendations are provided.