Patients' and therapists' shared and unique views of the therapeutic alliance: An investigation using confirmatory factor analysis in a nested design.

Analyzed large general factor found in measures of the therapeutic alliance by use of confirmatory factor analysis (CFA) in a nested design. Ratings by 38 therapists and their 144 patients on the California Psychotherapy Alliance Scales (CALPAS), the Revised Penn Helping Alliance Questionnaire (HAQ-R), and the Working Alliance Inventory (WAI) were adjusted for therapist effects. A set of models for S and therapist ratings was tested with CFA, and a 3-factor model was confirmed, x–2(4)?=? 7.19, p> .13; GFI?=?.98; RMSR?=?.02; CFI?=?1.0. A shared-view factor (best represented by HAQ-R) accounted for 44% of patients' and 27% of therapists' variance. Unique factors accounted for 56% of therapists' and 43% of Ss' variance. S views split between HAQ and WAI factors; The WAI factor was most expressive of therapist views. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Measuring motivations for intercollegiate athlete alcohol use: A confirmatory factor analysis of the Drinking Motives Measure.

This study examined the psychometric properties of the Drinking Motives Measure (DMM) on a sample of 227 collegiate athletes. Confirmatory factor analyses indicated that the 4-factor structure of the DMM provided a better fit than either 2- or 1-factor models, but the overall fit of the 4-factor model was moderate at best. A revised 3-factor model consistent with prior research (M. L. Cooper, M. Russell, J. B. Skinner, & M. Windle, 1992) provided the best fit. Hierarchical multiple regression analyses indicated that the 3 DMM factors included in the revised model accounted for 17%-21% of the unique variance on alcohol consumption variables. Results provide preliminary evidence supporting the internal consistency, construct validity, and convergent validity of the revised 3-factor DMM with collegiate athletes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Factorial invariance across sex of the Form V of the Sensation-Seeking Scale.

The factorial properties across sex of the Sensation-Seeking Scale—Form V were examined in a sample of 335 female and 363 male Australian Ss aged 17–60 yrs. A 4-factor solution was applied to the data of both sex groups to test the correspondence with M. Zuckerman's (1977) postulated 4 distinct dimensions of sensation seeking. The results generally support the existence of the 4 dimensions; however, the percentage of total variance accounted for was only 33% for females and 31% for males. No additional factor accounted for more than 4% of total variance. The factor structures of the male and female samples were very similar. Attention is drawn to items that do not load significantly on the expected factor, multifactorial items, and items with loadings that suggest sex differences in the connotations of item content. (7 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Confirmatory Factor Analysis of the Psychopathy Checklist: Screening Version in Offenders With Axis I Disorders.

One hundred forty-nine inpatients within a maximum security psychiatric facility were assessed with the Psychopathy Checklist: Screening Version (PCL:SV; S. D. Hart, D. N. Cox, & R. D. Hare, 1995). Within the total sample, 68% had a psychotic disorder and 30% met criteria for psychopathy. Using confirmatory factor analysis, the authors tested the 2-factor PCL:SV model of psychopathy and recent 3- and 4-factor models. Results indicated good fit for each model, with the 4-factor model showing best overall fit. Structural equation modeling was used to determine which psychopathy factors predicted 6-month follow-up of inpatient aggression. The 2-, 3-, and 4-factor models, respectively, accounted for 16%.27%. and 3l% of the variance in aggression. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

WISC-R factor structures among Anglos, Blacks, Chicanos, and Native-American Papagos.

Compared WISC-R factor structures for Anglo, Black, Chicano, and Native-American Papago children from Pima County, Arizona. The samples were randomly selected from school enrollment rosters and stratified by ethnicity, grade level (1st, 3rd, 5th, 7th, and 9th), sex, and urban–rural residence (950 Ss). Application of 2 objective procedures for determining the appropriate number of factors for each group suggested a 3-factor solution for Anglos, a 2- or 3-factor solution for Chicanos depending on procedure used, and 2-factor solutions for Blacks and Native-American Papagos. The 2-factor solutions were highly similar for the 4 groups. The 3-factor solutions were similar for Anglos and Chicanos but were substantially different for the other groups. The groups were highly similar in terms of the proportion of variance accounted for by a general factor, and the Verbal–Performance scale distinction appeared equally appropriate for all groups. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Gambling Urge Scale: Development, Confirmatory Factor Validation, and Psychometric Properties.

The urge to gamble is a physiological, psychological, or emotional motivational state, often associated with continued gambling. The authors developed and validated the 6-item Gambling Urge Questionnaire (GUS), which was based on the 8-item Alcohol Urge Questionnaire (M. J. Bohn, D. D. Krahn, & B. A. Staehler, 1995), using 968 community-based participants. Exploratory factor analysis using half of the sample indicated a 1-factor solution that accounted for 55.18% of the total variance. This was confirmed using confirmatory factor analysis with the other half of the sample. The GUS had a Cronbach's alpha coefficient of .81. Concurrent, predictive, and criterion-related validity of the GUS were good, suggesting that the GUS is a valid and reliable instrument for assessing gambling urges among nonclinical gamblers. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Factor analysis of the Wechsler Adult Intelligence Scale—Revised for persons 75 years and older.

We factor analyzed the Wechsler Adult Intelligence Scale—Revised (WAIS—R) protocols of 130 normal elderly. For age and education, Ms?=?81.24 years (SD?=?5.24) and 9.54 years (SD?=?2.50). Results indicated that the WAIS—R may be interpreted as a 1-, 2-, or 3-factor battery. In the 1-factor solution, interpretative emphasis was placed on the Full Scale IQ as a measure of g. In the 2-factor solution, a Verbal Comprehension factor consisted of Information, Digit Span, Vocabulary, Comprehension, and Similarities. A Perceptual Organization factor comprised Block Design, Object Assembly, and Digit Symbol. In the 3-factor solution, the subtest alignments for the Verbal Comprehension and Perceptual Organization factors remained highly similar, whereas Arithmetic constituted a Freedom From Distractibility factor. Overall, 1- or 2-factor models seem to offer the most plausible and parsimonious structures for this sample. Seven subtests had high or intermediate levels of specific variance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Psychometric Analysis of the Revised Memory and Behavior Problems Checklist: Factor Structure of Occurrence and Reaction Ratings.

A modified version of the Revised Memory and Behavior Problems Checklist (RMBPC; L. Ten et al, 1992) was administered across 6 different sites to 1,229 family caregivers of community-dwelling adults with dementia. The total sample was divided randomly into 2 subsamples. Principal components analyses on occurrence responses and reaction ratings from the first subsample resulted in a 3-factor solution that closely resembled the originally proposed dimensions (memory-related problems, disruptive behaviors, and depression). Confirmatory factor analyses on data from the second subsample indicated adequate fit for the 3-factor model. Correlations with other caregiver and care-recipient measures supported the convergent and discriminant validity of the RMBPC measures. In addition, female caregivers and White caregivers reported more problems, on average, than male caregivers and African American caregivers, respectively. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Number of factors in the personality sphere: Does increase in factors increase predictability of real-life criteria?

Many researchers support a 5- to 8-factor personality theory; Cattell urges a 16-factor system. Factor analysis has been unable to resolve this controversy. Hence, the degree to which 6 and 16 factors related to a proposed new criterion (real-life data) was evaluated in 16 data sets. When factors were increased from 6 to 16, 88% of the studies showed a significant increase in R. The percentage of variance accounted for, after shrinking the Rs, was doubled. We concluded that the 5- to 8-factor position has limited usefulness; use of more factors is strongly supported. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Development and validation of the Smoking Expectancy Scale for Adolescents.

This study assessed the factor structure, internal consistency, and concurrent validity of the Smoking Expectancies Scale for Adolescents (SESA) using 717 Australian adolescents (87% nonsmokers, 11% current smokers, and 2% ex-smokers). Exploratory factor analysis of SESA yielded 8 factors. Confirmatory factor analysis indicated that the 8-factor model, and also a 2nd-order cost-benefit model, fit the data significantly better than 4 alternatives. Validation analyses revealed the 8-factor model explained 26% to 32% of the variance in adolescent cigarette use, smoking intentions, smoking subjective norms, and peer smoking. The 2nd-order model explained 12% to 17% of the variance in these same variables. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Comparison of factor structure models for the Beck Depression Inventory--II.

Factor analyses of the Beck Depression Inventory--II (A. T. Beck, R. A. Steer, & G. K. Brown, 1996) have frequently produced 2 different 2-factor oblique structures. The author used confirmatory factor analyses to compare these structures with a general-factor model with 2 orthogonal group factors. The general-factor model fit as well as or better than the 2-factor models when applied to item data from previous studies (3 clinical and 2 college samples). Communalities associated with the General Depression factor ranged from 71% to 82%. Cognitive and Somatic group factors were indicative of intropunitiveness and fatigue. It was concluded that the general-factor model gives an acceptable empirical explanation of item covariance structure and offers a conceptual interpretation that is well suited to clinical practice and research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Some problems in the nonorthogonal analysis of variance.

Contends that nonorthogonal analysis of variance has been much misunderstood by psychologists, and as a result there has been considerable controversy as to the appropriate methods of analysis. These problems traditionally associated with the nonorthogonal multifactor analysis of variance are rather easily resolved by viewing the analysis of variance (either orthogonal or nonorthogonal) as a series of model comparisons. From this point of view, the analysis of highly confounded designs is seen to yield results that correspond to those that a purely logical analysis would suggest. A logical flow of comparisons and decisions is developed for both the 2- and 3-factor designs that, although more complicated than procedures previously proposed, seems necessary for drawing proper inferences. It is further shown that there is no logical difference between orthogonal and nonorthogonal analysis of variance. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A psychometric evaluation of the Beck Depression Inventory–II.

This article provides psychometric information on the second edition of the Beck Depression Inventory (BDI–II; A. T. Beck, R. A. Steer, & G. K. Brown, 1996), with respect to internal consistency, factorial validity, and gender differences. Both measures demonstrated high internal reliability in the full student sample. Significant differences between the mean BDI and BDI-II scores necessitated the development of new cutoffs for analogue research on the BDI–II. Results from exploratory and confirmatory factor analyses indicated that a 2-factor solution optimally summarized the data for both versions of the inventory and accounted for a cumulative 41% and 46% of the common variance in BDI and BDI–II responses, respectively. These factor solutions were reliably cross-validated, although the importance of each factor varied by gender. The authors conclude that the BDI–II is a stronger instrument than the BDI in terms of its factor structure. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Latent structure of the Postconcussion Syndrome Questionnaire.

The underlying structure of the Postconcussion Syndrome Questionnaire (PCS) was evaluated in a large sample of medical and psychiatric patients. Three potentially viable models were generated using exploratory factor analysis with half of the sample. The other half evaluated the 3-, 4-, and 5-factor models using confirmatory factor analytic procedures. The factor analyses generated compelling data for a 5-factor model for the PCS questionnaire. However, internal consistency for each of the factors argued in favor of the 3-factor model. Balancing internal consistency, confirmatory factor analyses, and parsimony resulted in endorsement of a 4-factor solution for the PCS questionnaire for this sample. The factors are best described as clusters of psychological, somatic, cognitive, and infrequent complaints. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Orthogonal higher order structure and confirmatory factor analysis of the French Wechsler Adult Intelligence Scale (WAIS-III).

According to the most widely accepted Cattell–Horn–Carroll (CHC) model of intelligence measurement, each subtest score of the Wechsler Intelligence Scale for Adults (3rd ed.; WAIS–III) should reflect both 1st- and 2nd-order factors (i.e., 4 or 5 broad abilities and 1 general factor). To disentangle the contribution of each factor, we applied a Schmid–Leiman orthogonalization transformation (SLT) to the standardization data published in the French technical manual for the WAIS–III. Results showed that the general factor accounted for 63% of the common variance and that the specific contributions of the 1st-order factors were weak (4.7%–15.9%). We also addressed this issue by using confirmatory factor analysis. Results indicated that the bifactor model (with 1st-order group and general factors) better fit the data than did the traditional higher order structure. Models based on the CHC framework were also tested. Results indicated that a higher order CHC model showed a better fit than did the classical 4-factor model; however, the WAIS bifactor structure was the most adequate. We recommend that users do not discount the Full Scale IQ when interpreting the index scores of the WAIS–III because the general factor accounts for the bulk of the common variance in the French WAIS–III. The 4 index scores cannot be considered to reflect only broad ability because they include a strong contribution of the general factor. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

WAIS-R Factor Structure in Alzheimer's Disease Patients: A Comparison of Alternative Models and an Assessment of Their Generalizability.

The WAIS-R is often used in neuropsychological evaluations of individuals with probable Alzheimer's disease (AD), but its factor structure in this population is unknown. Moreover, theories and past research findings make competing predictions concerning its structure. Using confirmatory factor analysis, the authors compared 5 alternative WAIS-R factor models among 516 AD patients: 1-factor (Spearman's g) and 2-factor (Verbal IQ and Performance IQ) models; a 3-factor model including Verbal Comprehension (VC), Perceptual Organization (PO), and Freedom From Distractibility (FD) factors; a 3-factor model in which Digit Symbol loads on PO rather than FD; and a 3-factor model in which Digit Symbol loads on both PO and FD. Results favored the 3-factor model in which Digit Symbol loads on PO rather than FD. Moreover, this model fit the data best among subsamples of patients defined by age, dementia severity, years of education, and gender. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Processes underlying divergent thinking and problem solving.

A battery of problem-solving and divergent-thinking tasks was administered to 91 5th graders from a middle-class background. The purpose was to attempt identification of a factor that could be labeled "problem solving" and be distinct from divergent-thinking factors. In exploratory factor analyses, principal axis, alpha, and maximum-likelihood factor procedures with orthogonal and oblique rotations were computed. The 3-factor solutions across all factor methods and rotations were consistent. In addition to a major ideational fluency factor and a small school achievement factor, a factor consisting of tasks requiring Ss to analyze given problem conditions and sequence steps to achieve a stated goal was identified. This factor accounted for 20–30% of the total variance and was labeled a problem-solving factor. Results are discussed in terms of possible psychological processes underlying divergent thinking and problem solving. (23 ref) (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The Satisfaction With Therapy and Therapist Scale--Revised (STTS-R) for group psychotherapy: Psychometric properties and confirmatory factor analysis.

Patients' level of satisfaction with their therapeutic experience is a concept that is important for understanding treatment efficacy; however, patient satisfaction has received little empirical attention. The Satisfaction With Therapy and Therapist Scale (STTS) developed for group psychotherapy by T. P. S. Oei and G. J. Shuttlewood (1999) was designed to assess patients' level of satisfaction with their therapeutic endeavor. This article aims to strengthen the STTS's psychometric properties by using confirmatory factor analysis (CFA) with a large sample of patients with mood and anxiety disorders. Outpatients (N = 344) took part in the study. Exploratory factor analysis indicated 2 conceptually coherent factors that accounted for 66.9% of the variance. The 2 factors, which were similar to those found in Oei and Shuttlewood (1999), namely, Satisfaction With Therapy and Satisfaction With Therapist, were replicated. CFA revealed a 2-factor solution to be the best-fitting model. Overall, this article demonstrated that the STTS-R has sound psychometric properties and would serve as a useful instrument in assessing a patient's level of satisfaction with both group therapy and therapist in research as well as in clinical settings. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Factor structure of the Children’s Perception of Interparental Conflict Scale for studies of youths with externalizing behavior problems.

The assessment of children’s perception of marital conflict is an important area of research related to family relations, children’s cognitions about self, and the development of psychopathology. The leading instrument in this domain is the Children’s Perception of Interparental Conflict Scale (CPIC; J. H. Grych, M. Seid, & F. D. Fincham, 1992). It has 48 items organized into 9 conceptual designed subscales, with reports of 3-factor higher order structure to the 9 subscales. However, the 3-factor solution does not capture all 9 subscales well. Further, items have never been subjected to factor analysis to evaluate the best fitting factor structure at the item level. Doing so is particularly important when bringing the scale into new populations such as children with attention-deficit/hyperactivity disorder (ADHD) or disruptive behavior disorders. In the present study, 2 samples of children (total N = 1,190; ages 6–18 years) completed the CPIC. An exploratory factor analysis in Sample 1 (from a clinical study of ADHD and non-ADHD youths) yielded 4 interpretable factors. A confirmatory factor analysis in Sample 2 (a population sample of twins) confirmed the generalizability of the solution with an acceptable fit, although 1 item was dropped. The final solution used 38 of the 48 items. The 4-factor solution captured a Conflict Properties factor, two appraisal factors labeled Threat to Self and Self-Blame, and a Triangulation/Stability factor that included elements of appraisal and content. The authors concluded that the item-based 4-factor solution to the CPIC is preferable to the 9-factor or 3-factor formulation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Assessment of depressive symptoms during inpatient rehabilitation for spinal cord injury: Is there an underlying somatic factor when using the PHQ?

Objective: To test the hypothesis that a 2-factor solution, including a somatic factor, best accounts for the response pattern to the Patient Health Questionnaire-9 (PHQ-9) during inpatient rehabilitation after spinal cord injury (SCI). Research Design: 568 adults with traumatic SCI were administered the PHQ-9 during inpatient rehabilitation. The PHQ-9 was developed to identify depressive disorders based on DSM-IV criteria. Results: Maximum likelihood confirmatory factor analysis was used to compare unidimensional and alternative 2-factor models. The results suggested that the 2-factor solution with 3 somatic items (sleep disturbance, poor energy, appetite change) was a better solution than either a unidimensional model or 2-factor model that included psychomotor retardation as a fourth somatic item. The root mean square error of approximation with 3 somatic items fell within the acceptable range of less than .08 (.073). The 2 factors were highly correlated (.76) but within the acceptable range (less than .80). Conclusions: There may be 2 underlying factors with the PHQ-9, including a somatic factor, when measuring depressive symptoms during inpatient rehabilitation for SCI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)