Diagnostic Efficiency Statistics Research Articles

At the Core of Depression: A Diagnostic Interview of the Core Features of Depression

Introduction: Valid and reliable methods for diagnosing depression are essential. The present study aimed to test the performance of a new diagnostic interview for depression focusing on the core symptoms of depression. Method: We developed a diagnostic interview for depression: the CORE Diagnostic Interview, CORE-DI, which assesses each of the core features of depression on the four dimensions: quality, reactivity, globality, and fluctuations over time. The diagnostic performance of this interview was tested in a clinical study including 83 individuals presenting with various depressive symptoms, who were interviewed independently (1) by means of the CORE-DI and the Mini-International Neuropsychiatric Interview (M.I.N.I.), and (2) by highly skilled specialists in depression representing gold standard diagnoses. Results: We compared the outcome of the CORE-DI, the M.I.N.I., and the diagnosis made by clinicians, respectively, versus the gold standard diagnosis, using diagnostic efficiency statistics. The CORE-DI diagnosed depression with a high specificity (0.91, 95% CI: 0.85–0.97, for International Classification of Diseases [ICD]-10 criteria and 0.88, 95% CI: 0.81–0.95, for Diagnostic and Statistical Manual of Mental Disorders [DSM-5] criteria) compared to both M.I.N.I (specificity 0.44, 95% CI: 0.33–0.55) and clinical diagnoses (specificity 0.76, 95% CI: 0.67–0.85). The sensitivity of the CORE-DI was 0.61 (95% CI: 0.55–0.72) for ICD-10 criteria and 0.67 (95% CI: 0.57–0.77) for DSM-5 criteria. Discussion/Conclusion: The CORE-DI increased the specificity of the depression diagnosis substantially compared to clinical diagnoses and the diagnoses obtained by M.I.N.I. The results point to the usefulness of an elaborated and systematic assessment of the core symptoms in the examination of patients with depressive symptoms and thereby indicate a way for further development of specific diagnostic tools for depression in both clinical and research settings. However, it should be noted that the sensitivity of the CORE-DI was modest, and the psychometric properties of the CORE-DI might be different in other settings with higher or lower prevalence or severity of depressive symptoms.

Detection of Feigning of Different Symptom Presentations With the PAI and IOP-29.

This study examined the effectiveness of the negative distortion measures from the Personality Assessment Inventory (PAI) and Inventory of Problems-29 (IOP-29), by investigating data from a community and a forensic sample, across three different symptom presentations (i.e., feigned depression, posttraumatic stress disorder [PTSD], and schizophrenia). The final sample consisted of 513 community-based individuals and 288 inmates (total N = 801); all were administered the PAI and the IOP-29 in an honest or feigning conditions. Statistical analyses compared the average scores of each measure by symptom presentation and data source (i.e., community vs. forensic sample) and evaluated diagnostic efficiency statistics. Results suggest that the PAI Negative Impression Management scale and the IOP-29 are the most effective measures across all symptom presentations, whereas the PAI Malingering Index and Rogers Discriminant Function generated less optimal results, especially when considering feigned PTSD. Practical implications are discussed.

Patient Health Questionnaire (PHQ-9): A depression screening tool for people with epilepsy in Vietnam

BackgroundDepression is a common mental disorder in people with epilepsy. Depression has a negative impact on medical and surgical treatment of epilepsy thus affecting the quality of life. Despite its high prevalence, depression has been under-recognized and treated improperly. It may also lead to missed work, increased healthcare system utilization, and higher direct medical costs. ObjectivesThis study aimed to evaluate the accuracy of the Vietnamese Patient Health Questionnaire (PHQ-9) as a screening tool for depression in people with epilepsy. MethodsThis cross-sectional study was conducted prospectively at epilepsy clinic at Nguyen Tri Phuong hospital, Ho Chi Minh City, Viet Nam from December 2019 to March 2020. A total of 91 adult people with epilepsy were recruited. After completing the Vietnamese PHQ-9 questionnaires, each participant was interviewed in a structured clinical interview for DSM-5 (SCID-5) to establish a diagnosis of major depressive disorder. The diagnostic accuracy of the PHQ-9 was assessed using diagnostic efficiency statistics compared with the gold standard structured interview. ResultsThe prevalence of major depression in this sample was 25.3%. The areas under receiver operating characteristic (ROC) curve index of PHQ-9 had an estimated value of 0.91. The PHQ-9 at a cutoff point of 8 had the great overall balance of sensitivity (87.0%) and specificity (82.4%). At the cutoff point of 10, PHQ-9 had a higher specificity of 94.1%, but a lower sensitivity of 78.0%. ConclusionsThe Vietnamese version PHQ-9 is an efficient and valid screening tool for depression in people with epilepsy in clinic settings.

Clinical Associations Between Severity of Impulsivity, Psychiatric Morbidity, Dysfunctional Defences and Personality Disorder: A Comparative Study With Axis-I Disorders.

ObjectivePsychiatric morbidity, impulsive behaviour and use of dysfunctional and maladaptive defences are core features of personality disorder (PD). This study aims to evaluate the significance of the strength of the association between these three core dimensions and PD.MethodUsing a cross-sectional design, a sample of co-morbid Axis-I & -II disorders, and a sample of Axis-I disorders with no co-morbid PD were recruited at three general psychiatric mental health resource centres and then compared.PD as dependent variable was analysed both as a categorical and as a dimensional entity using the Structured Clinical Interview for DSM-IV. The Symptoms Checklist 90-R general severity index (GSI), the Barratt Impulsivity Scale (BIS) and the Defense Style Questionnaire (DSQ) were used to measure severity of psychiatric morbidity, impulsivity and defensive style, respectively.ResultsBIS was a highly significant predictor of categorical PD (β = .13, SE = .03, p < .001), but not GSI and DSQ. BIS and GSI significantly predicted PD as a dimensional construct (β = 0.32, SE = .08, t = 4.05, p < 0.001; and β = 5.04, SE = 1.54, t = 3.28, p = 0.002, respectively). The diagnostic efficiency statistics found that BIS had greater sensitivity (.82) and specificity (.79), and overall predictive power (.87) of correctly identifying true positive and true negative PD diagnosis compared to the other two measures.ConclusionsBIS may be used in routine clinical practice as a screening measure to identify the presence of PD in complex presentations.

Montreal Cognitive Assessment as Screening Measure for Mild and Major Neurocognitive Disorder in a Chilean Population

Background: The Montreal Cognitive Assessment (MoCA) is a sensitive screening instrument for mild neurocognitive disorder (mild NCD). However, cut-off scores and accuracy indices should be established using representative samples of the population. In this context, the aim of this study was to update the normative values, and diagnostic efficiency statistics of the MoCA to detect mild NCD in the Chilean population. Methods: This study included 226 participants from the north, center, and south of the country, classified into 3 groups: healthy elderly (HE; n = 113), mild NCD (n = 65), and major neurocognitive disorder (major NCD; n = 48). Results: The optimal cut-off score to discriminate mild NCD from HE participants was 20 points with a sensitivity of 82.8% and a specificity of 84.1%. The observed balance between sensitivity and specificity shows a good test performance either to confirm or discard a diagnosis. The cut-off between mild NCD and major NCD from HE participants was 19 points with 85.6% of sensitivity and 90.3% of specificity. Conclusion: Overall diagnostic accuracy can be considered as outstanding (AUC ≥0.904) when discriminating HE from both mild NCD and major NCD. These results showed that the MoCA is a suitable tool to identify mild NCD and major NCD.

Diagnostic accuracy of DSM-5 borderline personality disorder criteria: Toward an optimized criteria set

ObjectiveThe polythetic system used by the Diagnostic and Statistical Manual for Mental Disorders (DSM-5) for diagnosing borderline personality disorders (BPD) is far from optimal; however, accumulated research and clinical data are strong enough to warrant ongoing utilization. This study examined diagnostic efficiency of the nine DSM-IV BPD criteria, then explored the feasibility of an optimized criteria set in classifying BPD. MethodsAdults (N=1,623) completed the Structured Clinical Interviews for DSM-IV Axis II Disorders resulting in a BPD group (n=352) and an inpatient psychiatric control group (PC) with no personality disorders (n=1,271). Receiver operator characteristics and diagnostic efficiency statistics were calculated to ascertain the relative diagnostic efficiency of each DSM-5 BPD criterion in classifying BPD cases. ResultsAffective instability (Criterion 6) evidenced the strongest capacity to differentiate the groups (AUC = .84, SE = .01, p < .0001). Abandonment fears (Criterion 1), unstable relationships (Criterion 2), identity disturbance (Criterion 3), impulsivity (Criterion 4), and chronic emptiness (Criterion 7) yielded good-to-moderate discrimination (AUC range = .75-.79). A composite index of these six criteria yielded excellent accuracy (AUC = .98, SE = .002, p < .0001), sensitivity (SN=.99), and specificity (SP=.90). ConclusionsThe current findings add to evidence that affective instability is a useful gate criterion for screening, and the optimized criteria set evidences equivalent accuracy to the original 9 criteria, with a substantial reduction in estimated heterogeneity (from 256 combinations with the original set to 42 combinations with the optimized set).

The UCLA PTSD Reaction Index for DSM-5 Brief Form: A Screening Tool for Trauma-Exposed Youths

Children and adolescents who experience potentially traumatic events are at risk for developing posttraumatic stress disorder (PTSD). Although psychometrically sound measures are now available to assess these youths, brief tools are currently needed for screening purposes. Two studies were conducted to develop and validate the UCLA PTSD Reaction Index for DSM-5-Brief Form (RI-5-BF). Study 1 used item response theory models to derive the RI-5-BF from the UCLA PTSD Reaction Index for DSM-5 and assess its internal consistency using a sample of 486 trauma-exposed youths (mean age= 13.32 years, SD= 2.90) recruited through a practice research network. Study 2 used receiver operating characteristic analyses and diagnostic efficiency statistics to assess the discriminant-groups validity and clinical utility of the RI-5-BF in identifying children at different levels of PTSD risk using a sample of 41 treatment-seeking youths (mean age= 12.44 years, SD= 2.99). In study 1, item response theory models identified the 11 most informative items across their respective subscales. The RI-5-BF exhibited excellent internal consistency in both studies (α > .93). In study 2, receiver operating characteristic analyses indicated that an RI-5-BF score of 21 maximized sensitivity and specificity. Moreover, diagnostic likelihood ratios across multiple levels of scores provided support for the measure's clinical utility in identifying different levels of PTSD risk. These findings provide support for both the psychometric properties of the RI-5-BF as a brief screening measure for PTSD in children and adolescents and its utility for identifying youths meriting further assessment and consideration for treatment.

Differentiating bipolar disorder from borderline personality disorder: Diagnostic accuracy of the difficulty in emotion regulation scale and personality inventory for DSM-5

BackgroundConfusion abounds when differentiating the diagnoses of bipolar disorder (BD) from borderline personality disorder (BPD). This study explored the relative clinical utility of affective instability and self-report personality trait measures for accurate identification of BD and BPD. MethodsReceiver operator characteristics and diagnostic efficiency statistics were calculated to ascertain the relative diagnostic efficiency of self-report measures. Inpatients with research-confirmed diagnoses of BD (n = 341) or BPD (n = 381) completed the Difficulty in Emotion Regulation Scale (DERS) and Personality Inventory for DSM-5 (PID-5). ResultsThe total score for DERS evidenced relatively poor accuracy for differentiating the disorders (AUC = 0.72, SE = 0.02, p < .0001), while subscales of affective instability measures yielded fair discrimination (AUC range = 0.70–0.59). The PID-5 BPD algorithm (consisting of emotional lability, anxiousness, separation insecurity, hostility, depressivity, impulsivity, and risk taking) evidenced moderate-to-excellent accuracy (AUC = 0.83, SE = 0.04, p < .0001) with a good balance of specificity (SP = 0.79) and sensitivity (SN = 0.77). ConclusionFindings support the use of the PID-5 algorithm for differentiating BD from BPD. Furthermore, findings support the accuracy of the DSM-5 alternative model Criteria B trait constellation for differentiating these two disorders with overlapping features.

Confronting the Base Rate Problem: More Ups and Downs for Cognitive Scatter Analysis

Within the professional literature, it is frequently suggested that interpretation of cognitive profile scatter may be useful for generating a host of clinical inferences. To wit, Hale et al. (Psychology in the Schools, 45, 838–858, (2008)) posit that cognitive scatter is a defining characteristic of specific learning disability and that individuals with learning disabilities may have higher levels of scatter compared to normal controls. To investigate the tenability of this claim, the present study employed diagnostic efficiency statistics and other recommended psychometric methods (e.g., receiver operative characteristic curve, Bayesian nomogram) to test whether cognitive scatter could accurately distinguish between individuals with and without a known learning disability (LD) diagnosis in the Kaufman Assessment Battery for Children-Second Edition KABC-II; Kaufman and Kaufman (2004a) normative sample. Results indicated that increasing levels of cognitive profile scatter identified individuals with LD at no better than chance levels. The current negative results add to a growing corpus of research questioning the utility of many of the interpretive procedures that are utilized by school psychologists for commercial ability measures. In particular, it is suggested that clinicians who interpret cognitive profile scatter may risk diagnostic overconfidence and in the case of LD identification, unacceptable levels of false positive decisions attributable to error. Implications for evidence-based assessment in school psychology are discussed.

Clinical utility of the DSM-5 alternative model for borderline personality disorder: Differential diagnostic accuracy of the BFI, SCID-II-PQ, and PID-5

BackgroundWith the publication of DSM 5 alternative model for personality disorders it is critical to assess the components of the model against evidence-based models such as the five factor model and the DSM-IV-TR categorical model. This study explored the relative clinical utility of these models in screening for borderline personality disorder (BPD). MethodsReceiver operator characteristics and diagnostic efficiency statistics were calculated for three personality measures to ascertain the relative diagnostic efficiency of each measure. A total of 1653 adult inpatients at a specialist psychiatric hospital completed SCID-II interviews. Sample 1 (n=653) completed the SCID-II interviews, SCID-II Questionnaire (SCID-II-PQ) and the Big Five Inventory (BFI), while Sample 2 (n=1,000) completed the SCID-II interviews, Personality Inventory for DSM5 (PID-5) and the BFI. ResultsBFI measure evidenced moderate accuracy for two composites: High Neuroticism+ low agreeableness composite (AUC=0.72, SE=0.01, p<0.001) and High Neuroticism+ Low+Low Conscientiousness (AUC=0.73, SE=0.01, p<0.0001). The SCID-II-PQ evidenced moderate-to-excellent accuracy (AUC=0.86, SE=0.02, p<0.0001) with a good balance of specificity (SP=0.80) and sensitivity (SN=0.78). The PID-5 BPD algorithm (consisting of elevated emotional lability, anxiousness, separation insecurity, hostility, depressivity, impulsivity, and risk taking) evidenced moderate-to-excellent accuracy (AUC=0.87, SE=0.01, p<0.0001) with a good balance of specificity (SP=0.76) and sensitivity (SN=0.81). ConclusionsFindings generally support the use of SCID-II-PQ and PID-5 BPD algorithm for screening purposes. Furthermore, findings support the accuracy of the DSM 5 alternative model Criteria B trait constellation for diagnosing BPD. Limitations of the study include the single inpatient setting and use of two discrete samples to assess PID-5 and SCID-II-PQ.

Diagnostic Utility of the Pediatric Attention Disorders Diagnostic Screener

Objective: The Pediatric Attention Disorders Diagnostic Screener (PADDS) is an evidence-based screener of attention and executive functioning that combines computer-based Target Tests of Executive Function (TTEFs; Target Recognition, Target Sequencing, and Target Tracking) with parent and teacher behavioral reports to efficiently screen children ages 6 to 12 for ADHD. The present study is the first to examine the utility of the TTEFs in predicting ADHD status. Method: The PADDS TTEFs were administered to 76 children (age = 6-12) with ADHD and 76 matched controls. Logistic regression and diagnostic efficiency statistics were used to evaluate the ability of the three TTEFs to predicted ADHD status. Results: All three TTEFs significantly discriminated ADHD participants from controls, but each had a different diagnostic efficiency profile. Classification accuracy was improved when results of all three TTEFs were combined. Conclusion: The PADDS is a promising tool for quickly and reliably screening for ADHD in clinic and school settings.

Utility of the Neurobehavioral Symptom Inventory Validity-10 index to detect symptom exaggeration: An analogue simulation study

ABSTRACTThe Neurobehavioral Symptom Inventory (NSI) has been recommended by the interagency Traumatic Brain Injury (TBI) Outcome Workgroup as an outcome measure for TBI research. A new symptom exaggeration index—the NSI Validity-10—can be calculated from its items, but its utility has not been evaluated in a malingering simulation study. Data from a prior analogue study were reanalyzed to examine the NSI Validity-10 test properties. The data were from a sample of 85 Australian undergraduate students. A battery of measures was completed under 1 of 3 experimental conditions: control (i.e., honest responding, n = 24), feign postconcussional disorder (PCD; n = 29), and feign posttraumatic stress disorder (PTSD; n = 32). Participants who feigned PTSD or PCD had significantly higher scores on the NSI Validity-10 compared with controls. There were minimal differences between the 2 feigning groups. Using the combined data from the feigning groups and assuming a 35% symptom exaggeration base rate, the optimal NSI Validity-10 cutoff score was ≥10. This cutoff score identified “probable exaggeration” (sensitivity = .75, specificity = 1.0, positive predictive power = 1.0, negative predictive power = .88). Diagnostic efficiency statistics for 25% and 45% base rates were also generated. The cutoff score identified in this study is lower than previously reported. Its properties are promising, but its usage requires careful consideration.

Is the Eating Disorder Questionnaire-Online (EDQ-O) a valid diagnostic instrument for the DSM-IV-TR classification of eating disorders?

BackgroundThe Eating Disorder Questionnaire-Online (EDQ-O) is an online self-report questionnaire, which was developed specifically to provide a DSM-IV-TR classification of anorexia nervosa (AN), bulimia nervosa (BN), binge-eating disorder (BED), and eating disorder not otherwise specified (EDNOS), without using a face-to-face clinical interview. ObjectiveThe purpose of the present study was to examine the psychometric quality of the EDQ-O. MethodsThe validity of the EDQ-O was determined by examining the agreement with the diagnoses obtained from the Longitudinal, Expert, and All DATA (LEAD) standard. Participants included 134 new patients of a specialist center for eating disorders located in the Netherlands. ResultsAssessment of the validity of the EDQ-O yielded acceptable to good AUC (area under the receiver operating characteristic curve) values with a range from 0.72 to 0.83. Most other diagnostic efficiency statistics were also good except for a low sensitivity for AN (0.44), a low positive predictive value for BN (0.50), and a relatively low sensitivity for BED (0.66). ConclusionThe results of the present study suggest that the EDQ-O performs acceptably as a diagnostic instrument for all DSM-IV-TR eating disorder classifications. However, suggestions are made to further improve the validity of the EDQ-O.

A Primer on Receiver Operating Characteristic Analysis and Diagnostic Efficiency Statistics for Pediatric Psychology: We Are Ready to ROC

A Primer on Receiver Operating Characteristic Analysis and Diagnostic Efficiency Statistics for Pediatric Psychology: We Are Ready to ROC

A primer on receiver operating characteristic analysis and diagnostic efficiency statistics for pediatric psychology: we are ready to ROC.

To offer a practical demonstration of receiver operating characteristic (ROC) analyses, diagnostic efficiency statistics, and their application to clinical decision making using a popular parent checklist to assess for potential mood disorder. Secondary analyses of data from 589 families seeking outpatient mental health services, completing the Child Behavior Checklist and semi-structured diagnostic interviews. Internalizing Problems raw scores discriminated mood disorders significantly better than did age- and gender-normed T scores, or an Affective Problems score. Internalizing scores <8 had a diagnostic likelihood ratio <0.3, and scores >30 had a diagnostic likelihood ratio of 7.4. This study illustrates a series of steps in defining a clinical problem, operationalizing it, selecting a valid study design, and using ROC analyses to generate statistics that support clinical decisions. The ROC framework offers important advantages for clinical interpretation. Appendices include sample scripts using SPSS and R to check assumptions and conduct ROC analyses.

Validation of the telephone-administered PHQ-9 against the in-person administered SCID-I major depression module

BackgroundWe assessed item-to-item correspondence between the Patient Health Questionnaire-9 (PHQ-9) and the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I) major depression episode portion of the major depressive module. MethodFour hundred and ninety-eight soldiers in the Ohio National Guard were administered the PHQ-9 and SCID-I. Data were analyzed using chi-square analyses, logistic regression, receiver operating characteristic (ROC) curve analyses and diagnostic efficiency statistics. ResultsTo screen for depression effectively, results indicate use of the cardinal first two items, items representing fatigue, appetite and sleep changes with an item level cut-off point of two, and the item representing suicidal ideation with item level cut-off point of one. Further, total PHQ-9 scores significantly predicted SCID-I major depressive episode (MDE) and diagnosis (MDD) with moderate accuracy. Lastly, the cut-off total score of 10 had the optimal balance of sensitivity and specificity compared to other PHQ-9 scoring options. LimitationsDifferences in timeline of administration of the measures, differences in “worst episode” reference between the measures, and use of a specific military population are some of the limitations. ConclusionsThis validation study provides guidelines for the use of the telephone-administered PHQ-9 in assessing the lifetime prevalence of a major depressive episode and diagnosis in non-clinical populations, with implications for clinical use.

Diagnostic efficiency of the AUDIT-C in U.S. veterans with military service since September 11, 2001

BackgroundAlcohol screening with the 3-item alcohol use disorders identification test (AUDIT-C) has been implemented throughout the U.S. Veterans Health Administration. Validation of the AUDIT-C, however, has been conducted with samples of primarily older veterans. This study examined the diagnostic efficiency of the AUDIT-C in a younger cohort of veterans who served during Operation Enduring Freedom and/or Operation Iraqi Freedom (OEF/OIF). MethodsVeteran participants (N=1775) completed the alcohol use disorders identification test (AUDIT) and underwent the structured clinical interview for DSM-IV-TR for Axis I disorders (SCID) in research settings within four VA medical Centers. Areas under receiver operating characteristic curves (AUCs) measured the effiency of the full AUDIT and AUDIT-C in identifying SCID-based diagnoses of past year alcohol abuse or dependence. ResultsBoth measures performed well in detecting alcohol use disorders. In the full sample, the AUDIT had a better AUC (.908; .881–.935) than the AUDIT-C (.859; .826–.893; p<.0001). It is notable that this same result was found among men but not women, perhaps due to reduced power. Diagnostic efficiency statistics for the AUDIT and AUDIT-C were consistent with results from older veteran samples. The diagnostic efficiency of both measures did not vary with race or age. ConclusionsBoth the AUDIT and AUDIT-C appear to be valid instruments for identifying alcohol abuse or dependence among the most recent cohort of U.S. veterans with service during OEF/OIF within research settings.

An empirically derived approach to the classification and diagnosis of mood disorders.

This article describes a system for diagnosing mood disorders that is empirically derived and designed for its clinical utility in everyday practice. A random national sample of psychiatrists and clinical psychologists described a randomly selected current patient with a measure designed for clinically experienced informants, the Mood Disorder Diagnostic Questionnaire (MDDQ), and completed additional research forms. We applied factor analysis to the MDDQ to identify naturally occurring diagnostic groupings within the patient sample. The analysis yielded three clinically distinct mood disorder dimensions or spectra, consistent with the major mood disturbances included in the DSM and ICD over successive editions (major depression, dysthymia, and mania), along with a suicide risk index. Diagnostic criteria were determined strictly empirically. Initial data using diagnostic efficiency statistics supported the accuracy of the dimensions in discriminating DSM-IV diagnoses; regression analyses supported the discriminant validity of the MDDQ scales; and correlational analysis demonstrated coherent patterns of association with family history of mood disorders and functional outcomes, supporting validity. Perhaps most importantly, the MDDQ diagnostic scales demonstrated incremental validity in predicting adaptive functioning and psychiatric history over and above DSM-IV diagnosis. The empirically derived syndromes can be used to diagnose mood syndromes dimensionally without complex diagnostic algorithms or can be combined into diagnostic prototypes that eliminate the need for ever-expanding categories of mood disorders that are clinically unwieldy.

Development and Initial Validation of a Scale for Detecting Inconsistent Responding on the Personality Assessment Inventory–Short Form

The goal of this investigation was the development of an Inconsistency scale (ICN–SF) for the Personality Assessment Inventory–Short Form (PAI–SF). In Study 1, 503 inpatient profiles were randomly assigned to a derivation or cross-validation sample. Ten correlated item pairs were identified using the derivation sample and placed on the ICN–SF. Psychometric properties of the ICN–SF total scores were comparable in the derivation and cross-validation samples. Total ICN–SF scores in both samples were significantly lower than scores obtained from computer-generated random samples. Diagnostic efficiency statistics are reported using multiple cut-off scores at various base rate estimates. ICN–SF scores greater than 8 reasonably balanced sensitivity and specificity rates. This cutoff correctly classified 92% of the random protocols and inaccurately classified 9% of the patient protocols in Study 1. In Study 2, PAI–SF scores from 627 forensic and civil inpatients produced similar results, effectively identifying cases with elevated scores on the full-form Inconsistency scale. Overall the results of both studies suggest that the ICN–SF can aid examiners in assessing for inconsistent responding.

Validation of Proposed DSM-5 Criteria for Autism Spectrum Disorder

The primary aim of the present study was to evaluate the validity of proposed DSM-5 criteria for autism spectrum disorder (ASD). We analyzed symptoms from 14,744 siblings (8,911 ASD and 5,863 non-ASD) included in a national registry, the Interactive Autism Network. Youth 2 through 18 years of age were included if at least one child in the family was diagnosed with ASD. Caregivers reported symptoms using the Social Responsiveness Scale and the Social Communication Questionnaire. The structure of autism symptoms was examined using latent variable models that included categories, dimensions, or hybrid models specifying categories and subdimensions. Diagnostic efficiency statistics evaluated the proposed DSM-5 algorithm in identifying ASD. A hybrid model that included both a category (ASD versus non-ASD) and two symptom dimensions (social communication/interaction and restricted/repetitive behaviors) was more parsimonious than all other models and replicated across measures and subsamples. Empirical classifications from this hybrid model closely mirrored clinical ASD diagnoses (90% overlap), implying a broad ASD category distinct from non-ASD. DSM-5 criteria had superior specificity relative to DSM-IV-TR criteria (0.97 versus 0.86); however sensitivity was lower (0.81 versus 0.95). Relaxing DSM-5 criteria by requiring one less symptom criterion increased sensitivity (0.93 versus 0.81), with minimal reduction in specificity (0.95 versus 0.97). Results supported the validity of proposed DSM-5 criteria for ASD as provided in Phase I Field Trials criteria. Increased specificity of DSM-5 relative to DSM-IV-TR may reduce false positive diagnoses, a particularly relevant consideration for low base rate clinical settings. Phase II testing of DSM-5 should consider a relaxed algorithm, without which as many as 12% of ASD-affected individuals, particularly females, will be missed. Relaxed DSM-5 criteria may improve identification of ASD, decreasing societal costs through appropriate early diagnosis and maximizing intervention resources.