Factorial Structure of Measures Assessing the Energetic Capacities of Trained Individuals

1984 ◽  
pp. 121-125
Author(s):  
S. Heimer ◽  
R. Medved ◽  
K. Komirović
Keyword(s):  
Factorial Structure

The Need Inventory of Sensation Seeking (NISS)

2012 ◽  
Vol 28 (1) ◽  
pp. 11-18 ◽  
Author(s):  
Marcus Roth ◽  
Philipp Hammelstein
Keyword(s):  
Sensation Seeking ◽  
Reliability And Validity ◽  
Assessment Method ◽  
Factorial Structure ◽  
Conventional Methods ◽  
New Research ◽  
Sensation Seeking Scale ◽  
Temperamental Trait ◽  
Nonclinical Study

Based on the conception of sensation seeking as a need rather than a temperamental trait ( Hammelstein, 2004 ), we present a new assessment method, the Need Inventory of Sensation Seeking (NISS), which is considered to assess a motivational disposition. Three studies are presented: The first examined the factorial structure and the reliability of the German versions of the NISS; the second study compared the German and the English versions of the NISS; and finally, the validity of the NISS was examined in a nonclinical study and compared to the validity of conventional methods of assessing sensation seeking (Sensation Seeking Scale – Form V; SSS-V). Compared to the SSS-V, the NISS shows better reliability and validity in addition to providing new research possibilities including application in experimental areas.

Construction and Validation of a Short Adjectives Checklist to Measure Big Five (SACBIF)

1996 ◽  
Vol 12 (1) ◽  
pp. 33-42 ◽  
Author(s):  
Marco Perugini ◽  
Luigi Leone
Keyword(s):  
Construct Validity ◽  
Psychometric Properties ◽  
Big Five ◽  
Factor Model ◽  
Five Factor Model ◽  
Selection Procedure ◽  
Factorial Structure ◽  
Personality Dimensions

The aim of this contribution is to present a new short adjective-based measure of the Five Factor Model (FFM) of personality, the Short Adjectives Checklist of BIg Five (SACBIF). We present the various steps of the construction and the validation of this instrument. First, 50 adjectives were selected with a selection procedure, the “Lining Up Technique” (LUT), specifically used to identify the best factorial markers of the FFM. Then, the factorial structure and the psychometric properties of the SACBIF were investigated. Finally, the SACBIF factorial structure was correlated with some main measures of the FFM to establish its construct validity and with some other personality dimensions to investigate how well these dimensions could be represented in the SACBIF factorial space.

Factorial Structure of the SCAS and Its Relationship With the SDQ

2013 ◽  
Vol 29 (1) ◽  
pp. 28-35 ◽  
Author(s):  
Daniela Di Riso ◽  
Daphne Chessa ◽  
Andrea Bobbio ◽  
Adriana Lis
Keyword(s):  
Age Differences ◽  
Convergent Validity ◽  
Factor Model ◽  
Community Sample ◽  
Anxiety Symptoms ◽  
Factorial Structure ◽  
Confirmatory Factor ◽  
Culturally Based ◽  
Positive Correlations ◽  
Italian Children

The factorial structure of the Spence Children’s Anxiety Scale (SCAS; Spence, 1997 ) was examined in a community sample of 1,397 Italian children from 8 to 10 years old. Sex and age differences as regards anxiety symptoms were also analyzed. The convergent validity of the SCAS was explored through correlations with the Strengths and Difficulties Questionnaire (SDQ; Goodman, 1997 ). The use of confirmatory factor analysis supported the six correlated factor model of the SCAS with only minor differences compared to the original work by Spence (1997 ), and it was therefore named SCAS-it. Modifications to the original SCAS were supported by methodologically, theoretically, and culturally based arguments. The internal consistency of the SCAS-it was acceptable. Females displayed significantly higher levels of anxiety symptoms than males, while age differences were nonsignificant. Positive correlations were found between the SCAS-it and selected subscales of the SDQ. The results support the SCAS model, with few exceptions that do not threaten the utility of Spence’s tool.

Equivalent Factorial Structure of the Brief Symptom Inventory (BSI) in Clinical and Nonclinical Jordanian Populations

2010 ◽  
Vol 26 (2) ◽  
pp. 116-121 ◽  
Author(s):  
Fawzi S. Daoud ◽  
Amjed A. Abojedi
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Exploratory Factor Analysis ◽  
Clinical Sample ◽  
Brief Symptom Inventory ◽  
Factorial Structure ◽  
Symptom Inventory ◽  
Confirmatory Factor ◽  
Item Checklist ◽  
General Psychological Distress

This study investigates the equivalent factorial structure of the Brief Symptom Inventory (BSI) in clinical and nonclinical Jordanian populations, using both exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). The 53-item checklist was administered to 647 nonclinical participants and 315 clinical participants. Eight factors emerged from the exploratory factor analysis (EFA) for the nonclinical sample, and six factors emerged for the clinical sample. When tested by parallel analysis (PA) and confirmatory factor analysis (CFA), the results reflected a unidimensional factorial structure in both samples. Furthermore, multigroup CFA showed invariance between clinical and nonclinical unidimensional models, which lends further support to the evidence of the unidimensionality of the BSI. The study suggests that the BSI is a potentially useful measure of general psychological distress in clinical and nonclinical population. Ideas for further research are recommended.

The childhood inventory of daily stressors (IIEC): Factorial structure

2005 ◽  
Author(s):  
J. Fernandez ◽  
M. Escobar ◽  
A. Florin ◽  
M. Trianes ◽  
M. Blanca
Keyword(s):  
Factorial Structure ◽  
Daily Stressors

Emotion information processing as a new component of emotional intelligence: Theoretical framework and empirical evidence

2021 ◽  
pp. 089020702110076
Author(s):  
Marina Fiori ◽  
Shagini Udayar ◽  
Ashley Vesely Maillefer
Keyword(s):  
Emotional Intelligence ◽  
Information Processing ◽  
Incremental Validity ◽  
Stressful Situation ◽  
Factorial Structure ◽  
Ability Emotional Intelligence ◽  
Processing Component ◽  
Overall Performance ◽  
The Relationship

The relationship between emotional intelligence (EI) and emotion information processing (EIP) has received surprisingly little attention in the literature. The present research addresses these gaps in the literature by introducing a conceptualization of emotional intelligence as composed of two distinct components: (1) EIK or emotion Knowledge component, captured by current ability emotional intelligence tests, related to top-down, higher order reasoning about emotions, and which depends more strongly on acquired and culture-bound knowledge about emotions; (2) EIP or emotion information Processing component, measured with emotion information processing tasks, requires faster processing and is based on bottom-up attention-related responses to emotion information. In Study 1 ( N = 349) we tested the factorial structure of this new EIP component within the nomological network of intelligence and current ability emotional intelligence. In Study 2 ( N =111) we tested the incremental validity of EIP in predicting both overall performance and the charisma of a presenter while presenting in a stressful situation. Results support the importance of acknowledging the role of emotion information processing in the emotional intelligence literature and point to the utility of introducing a new EI measure that would capture stable individual differences in how individuals process emotion information.

scholarly journals Measuring Subjective Sleep Quality: A Review

2021 ◽  
Vol 18 (3) ◽  
pp. 1082
Author(s):  
Marco Fabbri ◽  
Alessia Beracci ◽  
Monica Martoni ◽  
Debora Meneo ◽  
Lorenzo Tonetti ◽  
...  
Keyword(s):  
Construct Validity ◽  
Sleep Quality ◽  
Psychometric Properties ◽  
Internal Consistency ◽  
Self Report ◽  
Measurement Properties ◽  
Poor Sleep ◽  
Daily Routine ◽  
Factorial Structure ◽  
Poor Sleep Quality

Sleep quality is an important clinical construct since it is increasingly common for people to complain about poor sleep quality and its impact on daytime functioning. Moreover, poor sleep quality can be an important symptom of many sleep and medical disorders. However, objective measures of sleep quality, such as polysomnography, are not readily available to most clinicians in their daily routine, and are expensive, time-consuming, and impractical for epidemiological and research studies., Several self-report questionnaires have, however, been developed. The present review aims to address their psychometric properties, construct validity, and factorial structure while presenting, comparing, and discussing the measurement properties of these sleep quality questionnaires. A systematic literature search, from 2008 to 2020, was performed using the electronic databases PubMed and Scopus, with predefined search terms. In total, 49 articles were analyzed from the 5734 articles found. The psychometric properties and factor structure of the following are reported: Pittsburgh Sleep Quality Index (PSQI), Athens Insomnia Scale (AIS), Insomnia Severity Index (ISI), Mini-Sleep Questionnaire (MSQ), Jenkins Sleep Scale (JSS), Leeds Sleep Evaluation Questionnaire (LSEQ), SLEEP-50 Questionnaire, and Epworth Sleepiness Scale (ESS). As the most frequently used subjective measurement of sleep quality, the PSQI reported good internal reliability and validity; however, different factorial structures were found in a variety of samples, casting doubt on the usefulness of total score in detecting poor and good sleepers. The sleep disorder scales (AIS, ISI, MSQ, JSS, LSEQ and SLEEP-50) reported good psychometric properties; nevertheless, AIS and ISI reported a variety of factorial models whereas LSEQ and SLEEP-50 appeared to be less useful for epidemiological and research settings due to the length of the questionnaires and their scoring. The MSQ and JSS seemed to be inexpensive and easy to administer, complete, and score, but further validation studies are needed. Finally, the ESS had good internal consistency and construct validity, while the main challenges were in its factorial structure, known-group difference and estimation of reliable cut-offs. Overall, the self-report questionnaires assessing sleep quality from different perspectives have good psychometric properties, with high internal consistency and test-retest reliability, as well as convergent/divergent validity with sleep, psychological, and socio-demographic variables. However, a clear definition of the factor model underlying the tools is recommended and reliable cut-off values should be indicated in order for clinicians to discriminate poor and good sleepers.

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