Evaluating depression severity and remission with a modified Beck Depression Inventory

In an attempt to improve assessment of recovery from depression, a modified Beck Depression Inventory (mBDI) was created that permits endorsement of positive feelings in addition to depressive symptoms. In both normal and clinical samples, the mBDI showed evidence of reliability for measuring varying degrees of depression. In comparison to the original BDI, the mBDI did not significantly improve differentiation in depression severity among depressed individuals and assessment of remission of depressive symptoms. However, the mBDI was significantly better than the original BDI in detecting differences in depression level when overall depression severity was low. Clinical implications for evaluating remission of depression are discussed.     

Relationships between the Beck Depression Inventory and the Hamilton Psychiatric Rating Scale for Depression in depressed outpatients

The Beck Depression Inventory (BDI) and the Hamilton Psychiatric Rating Scale for Depression (HRSD) were used with 300 outpatients diagnosed with DSM-III major depression disorders. A principal-components analysis was performed on the intercorrelations among the 21 BDI and 24 HRSD symptoms. Three orthogonal components were found and interpreted as reflecting differences in self-report and clinical rating methods for measuring the severity of depression. The importance of using both self-reports and clinical ratings for evaluating depression in psychiatric outpatients was discussed.     

The Beck Depression Inventory as a Measure of Subjective Well-Being: A Cross-National Study

The present study examined the question whether the Beck Depression Inventory (BDI), which is one of the most widely used instruments to assess depression, can be used to measure differences in subjective well-being at national level. In order to establish the meaning of depression scores at country level, the functional equivalence (i.e., similarity of meaning) of depression scores at individual and country level was examined. Studies using the BDI in normal populations from 28 countries were collected. Depression showed the same correlates at individual and country level, which supports the functional equivalence of the BDI at the two levels. BDI scores and subjective well-being were then correlated with a number of country characteristics in order to test three theories of cross-national differences in subjective well-being. Livability theory stresses the importance of objective living conditions, comparison theory focuses on relative living conditions, and folklore theory states that cross-national differences can be explained by some national trait (e.g., beliefs and values concerning happiness). Cross-national differences in depression and subjective well-being could be explained by livability theory and folklore theory. BDI scores were negatively correlated with subjective well-being and other happiness-related variables. These findings suggest that depression had the same meaning at individual and country level and that depression is an adequate measure of (a lack of) subjective well-being at country level.     

Rasch analysis and item reduction of the hypomanic personality scale

The aim of the current study was to reduce the number of items in the 48-item hypomanic personality scale (HPS) and determine whether a unidimensional scale of the hypomanic trait could be derived. Previously collected HPS data from University students (n = 318) were applied to the Rasch model (one-parameter item response theory). Overall scale and individual item fit statistics were used to judge fit to the model and item maps employed to determine coverage of the trait. Cronbach’s Alpha and correlations with other questionnaires pre- and post-item reduction were evaluated. Rasch analysis indicated that the original HPS was not unidimensional, had significant redundancy and differential item functioning by age and gender. An iterative process of item reduction produced a 20-item HPS (HPS-20) that retained the concepts of the original HPS and had excellent fit to the Rasch model (χ² p = 0.27). Unidimensionality of the HPS-20 was confirmed. The traditional psychometric properties of the HPS-20 and coverage of the underlying hypomanic construct were similar to the original. It was possible to derive a unidimensional measure of the hypomanic trait. Further use of the HPS-20 is encouraged as it may increase understanding of the risk factors for affective disorders.     

Development of an abbreviated Personal Globe Inventory using item response theory: The PGI-Short

The responses of 2813 individuals to the Personal Globe Inventory (Tracey, 2002) were examined with the goal of developing a shorter, yet valid version of the scale using item response theory to guide the process. A random sample of 1000 individuals was used to select the best items and then the remaining 1813 were used as a validation sample to examine psychometric properties. For items to be included in the shortened form, the option characteristic curves had to conform to theory and there could be no presence of differential item functioning across either gender or ethnicity. The best 80 items were retained forming the PGI-Short. This instrument demonstrated excellent reliability and adherence to a circular model, there was no differential item functioning across either gender or ethnicity. The PGI-Short was supported as an alternative to the fuller version of the PGI.     

协单参数单维度Rasch模型的优势与意义

相比多参数多维度IRT模型通过增加参数的方式来提升模型拟合度和解释度，Rasch模型流派强调“理论驱动研究”和“数据符合模型”，推崇单参数单维度的测量模型能最大限度地减少额外因素对真实测量目的的影响和干扰，从而保证测量的客观性和准确性。Rasch模型关注测量目标与测量工具的对应关系，它的“简单”特性有助于研究者更准确地评估和解释被测目标与测量工具间的适配性，且在将非线性数据转化为等距数据时具有天然的优势。     

The derivation of some tests for the rasch model from the multinomial distribution

The present paper is concerned with testing the fit of the Rasch model. It is shown that this can be achieved by constructing functions of the data, on which model tests can be based that have power against specific model violations. It is shown that the asymptotic distribution of these tests can be derived by using the theoretical framework of testing model fit in general multinomial and product-multinomial models. The model tests are presented in two versions: one that can be used in the context of marginal maximum likelihood estimation and one that can be applied in the context of conditional maximum likelihood estimation.I am indebted to Norman Verhelst and Niels Veldhuijzen for their helpful comments. Requests for reprints should be sent to Cees A. W. Glas, Cito, PO Box 1034, 6801 MG Arnhem, THE NETHERLANDS.     

University Student Depression Inventory: Measurement model and psychometric properties

University Student Depression Inventory (USDI) was developed to assess the symptoms of depression among the university students. Considering the debilitating nature of depression among university students globally, USDI was translated in Persian and validated using university students from Iran. A battery including the Persian version of USDI and scales measuring suicide, depression, and stress was administered to a normative sample of 359 undergraduate students, and an additional clinical sample of 150 students referred to the university's mental health centre. The results supported the factor structure and the psychometric properties of the translated version. Confirmatory factor analysis upheld the previously reported three‐factor first‐order and one‐factor second‐order structure. The internal consistency, test‐retest reliability, and concurrent and discriminant validity of the Persian version were supported. Cut‐off points using receiver operating characteristic curve analysis were established to identify students at risk. Gender differences on the symptoms of depression were evident only in the normative sample, where male participants, compared with female students, had higher mean scores in lethargy, cognitive/emotion, and academic motivation subscales. The translated scale can be used with Persian‐speaking students in Iran and the neighbouring countries as well as those settled in the West to identify symptoms of depression for further evaluation and management.     

The underlying structure of the Beck Depression Inventory II: A multidimensional scaling approach

The purpose of the present study was to confirm Beck’s six symptom categorization of depression through the most recent version of Beck Depression Inventory (BDI-II) by employing a confirmatory multidimensional scaling (MDS). This analysis indicates two independent dimensions in the BDI-II. The disturbance domain dimension relates to the domains wherein the disturbances occur, and validates Beck’s six symptom categorization dividing the items into disturbances in basic need-satisfaction, energy regulation, focused attention, regulation of emotion, motivation, and cognitive distortion in self-evaluation. The level of arousal dimension relates to how the disturbances are expressed, namely in an under-active, regular, or over-active manifestation. The MDS solution suggests 18 (6 × 3) symptom areas of depression, and may serve as a guide for constructing additional items.     

The development of the Children's Empathic Attitudes Questionnaire using classical and Rasch analyses

Empathic responding is implicated in antisocial behaviors such as bullying, sexual offending, and violent crime. Identifying children and adolescents at risk for antisocial behavior and evaluating interventions designed to address problem behaviors require valid and reliable measures. Definitional controversies and limited measurement models have hindered measurement. This study describes the development and analysis of the Children's Empathic Attitudes Questionnaire (CEAQ) using both classical and modern techniques. Rasch analyses provided probabilistic results over large item and person groups, enabling meaningful inferences from patterns of responses at the construct level. Analyses of fifth through seventh graders' responses to the final version of the CEAQ provide support for its reliability, validity, and functionality. Four meaningful item clusters were identified, each reflecting more cognitively advanced empathic attitudes. These analyses suggest that the CEAQ provides a theoretically sound, hierarchically meaningful measure of empathic attitudes that will be useful in identification and intervention with children and adolescents at risk for antisocial behavior.     

主观评分中多面Rasch模型的应用

主观评分中存在的不一致性导致主观评分的信度降低。多面Rasch模型基于项目反应理论,可以应用于评分员效应的识别和消除,从而提高主观评分的信度。该文介绍多面Rasch模型的理论和应用框架,介绍了国外相关的典型应用,并且讨论了该模型的应用条件。     

HSK主观考试评分的Rasch实验分析

主观评分中存在的不一致性导致主观评分的信度降低。多面Rasch模型基于项目反应理论,可以应用于评分员效应的识别和消除,从而提高主观评分的信度。该文介绍多面Rasch模型的理论和应用框架,设计了基于该模型的HSK主观考试评分质量控制应用框架,利用HSK作文评分数据进行了实验验证。     

无领导小组讨论的多侧面Rasch模型应用*

采用项目反应理论(IRT)的多侧面Rasch模型(MFRM),分析评价中心技术中无领导小组讨论(LGD)的测评结果,探讨被试能力水平、评委评分宽严度、评分内部一致性、维度难度和评定等级等问题,进而讨论各种偏差。通过 MFRM 分析人事测评结果,可深入了解被试能力的真实差异、甑别维度难度、探查测评误差源,从而完善测评试题编制、评估或诊断评委合格性、提高测评维度与测评目的匹配性,为拓展项目反应理论在人事测评中的应用提供独特视角。     

Factor structure of the Beck Depression Inventory in a university sample

Factor analysis was performed on the Beck Depression Inventory with a university sample to examine its potential multidimensionality. A principal components analysis with an oblimin and varimax rotation produced a two-factor solution. These factors were labeled Cognitive-Affective and Physiological and accounted for approximately 39% of the common variance. This finding is consistent with multidimensionality of the inventory and with a similar study of college students. The commonalities of the two studies suggest the reliability (internal consistency) of the Cognitive-Affective and Physiological constructs among "minimally" depressed university samples.     

D-optimal design for the Rasch counts model with multiple binary predictors

In this paper we derive optimal designs for the Rasch Poisson counts model and its extended version of the (generalized) negative binomial counts model incorporating several binary predictors for the difficulty parameter. To efficiently estimate the regression coefficients of the predictors, locally D-optimal designs are developed. After an introduction to the Rasch Poisson counts model and its extension, we will specify these models as particular generalized linear models. Based on this embedding, optimal designs for both models including several binary explanatory variables will be presented. Therefore, we will derive conditions on the effect sizes for certain designs to be locally D-optimal. Finally, it is pointed out that the results derived for the Rasch Poisson models can be applied for more general Poisson regression models which should receive more attention in future psychological research.     

Scoring Depression on a Common Metric: A Comparison of EAP Estimation,Plausible Value Imputation,and Full Bayesian IRT Modeling

There are a growing number of item response theory (IRT) studies that calibrate different patient-reported outcome (PRO) measures, such as anxiety, depression, physical function, and pain, on common, instrument-independent metrics. In the case of depression, it has been reported that there are considerable mean score differences when scoring on a common metric from different, previously linked instruments. Ideally, those estimates should be the same. We investigated to what extent those differences are influenced by different scoring methods that take into account several levels of uncertainty, such as measurement error (through plausible value imputation) and item parameter uncertainty (through full Bayesian IRT modeling). Depression estimates from different instruments were more similar, and their corresponding confidence/credible intervals were larger when plausible value imputation or Bayesian modeling was used, compared to the direct use of expected a posteriori (EAP) estimates. Furthermore, we explored the use of Bayesian IRT models to update item parameters based on newly collected data.     

Loglinear Rasch models for the analysis of stability and change

Loglinear unidimensional and multidimensional Rasch models are considered for the analysis of repeated observations of polytomous indicators with ordered response categories. Reparameterizations and parameter restrictions are provided which facilitate specification of a variety of hypotheses about latent processes of change. Models of purely quantitative change in latent traits are proposed as well as models including structural change. A conditional likelihood ratio test is presented for the comparison of unidimensional and multiple scales Rasch models. In the context of longitudinal research, this renders possible the statistical test of homogeneity of change against subject-specific change in latent traits. Applications to two empirical data sets illustrate the use of the models.The author is greatly indebted to Ulf Böckenholt, Rolf Langeheine, and several anonymous reviewers for many helpful suggestions.     

纵向Rasch模型在大学新生适应性追踪研究中的应用

对1952名大学新生进行适应性调查,其中285人接受了2次以上的追踪调查,所得的多级评分重复测量数据采用纵向Rasch模型进行统计分析。研究应用SAS的GLIMMIX过程对多层Rasch模型参数估计作了新的尝试。结果表明：（1）新生在第一学年内,学习和情绪适应总体呈上升趋势,人际适应呈下降趋势;（2）不同个体入学时的适应状况差异显著,但是随时间变化的趋势、快慢相同;（3）学习适应分量表的项目稳定性较好,而人际、情绪适应的部分项目难度存在时间效应。研究结果对新生辅导具有启示意义     

Psychometric Meta‐Analysis of the English Version of the Beck Anxiety Inventory

This meta‐analysis reviewed 192 scholarly works from 1993 to 2013 using the Beck Anxiety Inventory (Beck & Steer, 1993 ). Aggregated internal consistency (coefficient alpha) was .91 (k = 117), and test–retest reliability was .65 (k = 18). Convergent comparisons were robust across 33 different anxiety instruments and the Beck Depression Inventory–II (Beck, Steer, & Brown, 1996 ). Structural validity primarily supported the original 2‐factor solution proposed by Beck and Steer ( 1993 ), and diagnostic accuracy varied according to the sample size and criterion cutoff score.