scholarly journals Eysenck’s Two Big Personality Factors and Their Relationship to Depression in Patients with Chronic Idiopathic Pain Disorder: A Clinimetric Validation Analysis

2012 ◽  
Vol 2012 ◽  
pp. 1-9 ◽  
Author(s):  
Per Bech ◽  
Marianne Lunde ◽  
Stine Bjerrum Møller
Keyword(s):  
Item Response ◽  
Principal Component ◽  
Pain Disorder ◽  
Anxiety And Depression ◽  
Personality Factors ◽  
Item Response Model ◽  
Idiopathic Pain ◽  
Positive Score ◽  
Hamilton Anxiety Scale ◽  
Neuroticism Scale

Aim. The clinimetric aspects of Eysenck’s two big personality factors (neuroticism and extraversion) were originally identified by principal component analysis but have been insufficiently analysed with item response theory models. Their relationship to states of melancholia and anxiety was subsequently analysed. Method. Patients with chronic idiopathic pain disorder were included in the study. The nonparametric item response model (Mokken) was compared to the coefficient alpha to validate the anxiety and depression subscales within the neuroticism scale and the extraversion and introversion subscales within the extraversion scale. When measuring states of depression and anxiety, the Melancholia Scale and the Hamilton Anxiety Scale were used. Results. We identified acceptable subscales of anxiety and depression in the Eysenck factor of neuroticism and extraversion versus introversion subscales within the Eysenck factor of extraversion. Focusing on the item of “Does your mood often go up and down?” we showed a statistically significant association with melancholia and anxiety for patients with a positive score on this item. Conclusion. Within the Eysenck factor of neuroticism it is important to differentiate between the anxiety and depression subscales. The clinimetric analysis of the Eysenck factor of extraversion identified valid subscales.

Effects of an Anxiety-Specific Psychometric Factor on Fear Conditioning and Fear Generalization

2017 ◽  
Vol 225 (3) ◽  
pp. 200-213 ◽  
Author(s):  
Christian Baumann ◽  
Miriam A. Schiele ◽  
Martin J. Herrmann ◽  
Tina B. Lonsdorf ◽  
Peter Zwanzger ◽  
...  
Keyword(s):  
Risk Factor ◽  
Anxiety Disorders ◽  
Fear Conditioning ◽  
Longitudinal Design ◽  
Principal Component ◽  
Anxiety And Depression ◽  
Specific Factor ◽  
High Anxious ◽  
Two Factors ◽  
Fear Generalization

Abstract. Conditioning and generalization of fear are assumed to play central roles in the pathogenesis of anxiety disorders. Here we investigate the influence of a psychometric anxiety-specific factor on these two processes, thus try to identify a potential risk factor for the development of anxiety disorders. To this end, 126 healthy participants were examined with questionnaires assessing symptoms of anxiety and depression and with a fear conditioning and generalization paradigm. A principal component analysis of the questionnaire data identified two factors representing the constructs anxiety and depression. Variations in fear conditioning and fear generalization were solely associated with the anxiety factor characterized by anxiety sensitivity and agoraphobic cognitions; high-anxious individuals exhibited stronger fear responses (arousal) during conditioning and stronger generalization effects for valence and UCS-expectancy ratings. Thus, the revealed psychometric factor “anxiety” was associated with enhanced fear generalization, an assumed risk factor for anxiety disorders. These results ask for replication with a longitudinal design allowing to examine their predictive validity.

The validity of the Melancholia Scale (MES) in predicting outcome of antidepressants in chronic idiopathic pain disorders

1991 ◽  
Vol 6 (3) ◽  
pp. 119-125 ◽  
Author(s):  
D Loldrup ◽  
M Langemark ◽  
HJ Hansen ◽  
M Kastrup ◽  
K Jeppesen ◽  
...  
Keyword(s):  
Construct Validity ◽  
Scale Score ◽  
Anxiety Scale ◽  
Full Recovery ◽  
Hamilton Depression Scale ◽  
Depressed Patients ◽  
Idiopathic Pain ◽  
Hamilton Anxiety Scale ◽  
Structure Evaluation ◽  
Hamilton Anxiety

SummaryIn patients with chronic idiopathic pain disorders we have analysed the construct validity of the Melancholia Scale as compared to the results with the scale in primary depression. The patients (n= 253) were treated in a placebo controlled trial with either clomipramine or mianserin independently of the Melancholia score. The construct validity of the Melancholia Scale was further analysed by the testing of the intensity model of depression versus anxiety using the Beck Depression Inventory, the Hamilton Anxiety Scale, the Spielberger State-Trait Anxiety Scale, and the Melancholia Scale. The construct validity in terms of scale homogeneity was analysed by Loevinger coefficients which can be considered as a latent structure evaluation. The Melancholia Scale showed acceptable homogeneity, while the Hamilton Anxiety Scale lacked sufficient homogeneity. In total, 33% of the patients had a score of 10 or more on the Melancholia Scale (corresponding to 13 or more on the Hamilton Depression Scale). The predictive validity of the Melancholia Scale was evaluated using active treatment versus placebo response after 6 weeks of therapy. It was shown that in patients with a Melancholia Scale score of 10 or more (corresponding to “less than major depression”) 72% had full recovery when treated with clomipramine, while 36% of the placebo treated patients obtained a full recovery (P≤0.05). The patients treated with mianserin obtained a full recovery in 52%. The group of patients with a Melancholia Scale score of 10 or more scored higher also on the anxiety scales indicating that the relation between depression and anxiety is a matter of severity. The depressed patients had significantly lower imipramine binding sites than the non-depressed patients.

scholarly journals Extensions of the skew-normal ogive item response model

2014 ◽  
Vol 28 (1) ◽  
pp. 1-23 ◽  
Author(s):  
Jorge Luis Bazán ◽  
Márcia D. Branco ◽  
Heleno Bolfarine
Keyword(s):  
Item Response ◽  
Response Model ◽  
Item Response Model ◽  
Skew Normal

Are Teachers' Unions Really to Blame? Collective Bargaining Agreements and Their Relationships with District Resource Allocation and Student Performance in California

2011 ◽  
Vol 6 (3) ◽  
pp. 354-398 ◽  
Author(s):  
Katharine O. Strunk
Keyword(s):  
Resource Allocation ◽  
Collective Bargaining ◽  
Student Performance ◽  
Item Response ◽  
Response Model ◽  
Item Response Model ◽  
Teachers Unions ◽  
Achievement Growth ◽  
Unique Measure ◽  
Level Student

Increased spending and decreased student performance have been attributed in part to teachers' unions and to the collective bargaining agreements (CBAs) they negotiate with school boards. However, only recently have researchers begun to examine impacts of specific aspects of CBAs on student and district outcomes. This article uses a unique measure of contract restrictiveness generated through the use of a partial independence item response model to examine the relationships between CBA strength and district spending on multiple areas and district-level student performance in California. I find that districts with more restrictive contracts have higher spending overall, but that this spending appears not to be driven by greater compensation for teachers but by greater expenditures on administrators' compensation and instruction-related spending. Although districts with stronger CBAs spend more overall and on these categories, they spend less on books and supplies and on school board–related expenditures. In addition, I find that contract restrictiveness is associated with lower average student performance, although not with decreased achievement growth.

scholarly journals Past Perspectives and New Opportunities for the Explanatory Item Response Model

2019 ◽  
Author(s):  
Yaacov Petscher ◽  
Donald Compton ◽  
Laura M. Steacy ◽  
Hannah Kinnon
Keyword(s):  
Individual Differences ◽  
Item Response ◽  
Word Reading ◽  
Random Effect ◽  
Error Variance ◽  
Item Response Model ◽  
Item Discrimination ◽  
Explanatory Variables ◽  
Item Level ◽  
Unique Item

Models of word reading that simultaneously take into account item-level and person-level fixed and random effects are broadly known as explanatory item response models (EIRM). Although many variants of the EIRM are available, the field has generally focused on the doubly explanatory model for modeling individual differences. Moreover, the historical application of the EIRM has been a Rasch version of the model where the item discrimination values are fixed at 1.0 and the random or fixed item effects only pertain to the item difficulties. The statistical literature has advanced to allow for more robust testing of observed or latent outcomes, as well as more flexible parameterizations of the EIRM. The purpose of the present study was to compare the observed and latent Rasch EIRM using commonly used statistical software (R and Mplus) and more broadly compare Rasch and 2PL EIRM when including person-level and item-level predictors. Results showed that not only was the error variance smaller in the unconditional 2PL EIRM compared to the Rasch EIRM due to including the item discrimination random effect, but that patterns of unique item-level explanatory variables difference between the two approaches. Results are interpreted within the context of what each statistical model affords to the opportunity for describing and explaining individual differences in word-level performance.

Psychology of Computer Use: VIII. Utilizing a Nonparametric Item Response Model to Develop Unidimensional Scales: Mokscal

1989 ◽  
Vol 68 (3) ◽  
pp. 987-1000 ◽  
Author(s):  
Elisabeth Tenvergert ◽  
Johannes Kingma ◽  
Terry Taerum
Keyword(s):  
Item Response ◽  
Goodness Of Fit ◽  
Functional Form ◽  
Search Procedure ◽  
Response Model ◽  
Scale Analysis ◽  
Item Response Model ◽  
Goodness Of Fit Test ◽  
Item Coefficient ◽  
Nonparametric Item Response

MOKSCAL is a program for the Mokken (1971) scale analysis based on a nonparametric item response model that makes no assumptions about the functional form of the item trace lines. The only constraint the Mokken model puts on the trace lines is the assumption of double monotony; that is, the item trace lines must be nondecreasing and the lines are not allowed to cross. MOKSCAL provides three procedures of scaling: a search procedure, an evaluation of the whole set of items, and an extension of an existing scale. All procedures provide a coefficient of scalability for all items that meet the criteria of the Mokken model and an item coefficient of scalability of every item. A test of robustness of the found scale can be performed to analyze whether the scale is invariant across different subgroups or samples. This robustness test may serve as a goodness-of-fit test for the established scale. The program is written in FORTRAN 77 and is suitable for both mainframe and microcomputers.

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