scholarly journals Psychometric properties of the COVID-19 associated PTSD-Scale

2021 ◽  
Vol 17 (10) ◽  
Author(s):  
Samer Jamil Rudwan
Keyword(s):  
Factor Analysis ◽  
Online Survey ◽  
Model Fit ◽  
Ptsd Symptoms ◽  
Post Traumatic Stress ◽  
Confirmatory Factor ◽  
Good Internal Consistency ◽  
Post Traumatic ◽  
Ptsd Scale ◽  
High Degree

This study aimed to create a scale to measure post-traumatic stress disorder (PTSD) symptoms related to the COVID 19 crisis. Based on the available studies, the Davidson PTSD scale dimensions were used in this online survey. Accordingly, a new scale was designed based on the clinical characteristics of the symptoms of the PTSD, so questions revolved around the possible psychological PTSD symptoms associated with COVID 19. Descriptive approach was used. The study involved 423 participants from the Sultanate of Oman, of whom, 219 were male and 204 were female. Statistical analyses of the scale were conducted using reliability, criterion-related validity, as well as exploratory and confirmatory factor analysis. The factor analysis revealed three factors to which 15 items of 17 items were loaded that reflect the clinical features of PTSD symptoms. Overall, the scale showed good internal consistency and stability, with relatively good correlations between the items within the factors. The analysis of the confirmation factors led to model fit validation with 14 items, with the results showing a high degree of conformity. Accordingly, the results were discussed, and further studies suggested to further verify and confirm the scale validity.

scholarly journals Measuring adolescent attitudes towards dementia: The revalidation and refinement of the A-ADS

2020 ◽  
pp. 135910532095347
Author(s):  
Nicolas Farina ◽  
Alys W Griffiths ◽  
Laura J Hughes ◽  
Sahdia Parveen
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Concurrent Validity ◽  
Principal Component ◽  
Model Fit ◽  
Single Factor ◽  
Confirmatory Factor ◽  
Adolescent Attitudes ◽  
Good Internal Consistency

The A-ADS is one the first validated measures of attitudes of dementia in adolescents, though further validation is needed. 630 adolescents were recruited from secondary schools in England. A Principal Component Analysis was completed ( n = 230) followed by a Confirmatory Factor Analysis ( n = 400). Reducing the A-ADS into a single factor, 13-item measure (Brief A-ADS) improved the model fit of the measure (χ2 = 182.75, DF = 65, CMIN/DF = 2.81, p < 0.001, CFI = 0.90, RMSEA = 0.07). The scale demonstrated good internal consistency, good predictive and concurrent validity. Building on the validation of the A-ADS, the Brief A-ADS is suitable to capture attitudes towards dementia amongst adolescents.

scholarly journals Post-Traumatic Outcomes among Survivors of the Earthquake in Central Italy of August 24, 2016. A Study on PTSD Risk and Vulnerability Factors

2021 ◽  
Author(s):  
Olimpia Pino ◽  
Annalisa Pelosi ◽  
Valentina Artoni ◽  
Massimo Mari
Keyword(s):  
Central Italy ◽  
Ptsd Symptoms ◽  
Post Traumatic Stress ◽  
Vulnerability Factors ◽  
Five Factors ◽  
Confirmatory Factor ◽  
Post Traumatic ◽  
Logistic Regressions ◽  
Estimate Prevalence

AbstractCentral Italy suffered from the earthquake of 2016 resulting in great damage to the community. The purpose of the present study was to determine the long-term traumatic outcomes among the population. A preliminary study aimed at obtaining the Italian translation of the first 16 item of HTQ IV part [1] which was administered, 20 months after the disaster, at 281 survivors. In backward stepwise logistic regressions models, we estimated among the respondent’s characteristics and event-related variables the best predictors of Post-Traumatic Stress Disorder (PTSD).A Confirmatory Factor Analysis (CFA) revealed a HTQ five-factors solution as best model, with satisfactory indexes of fit. HTQ held a positive correlation with both the SQD-P (r = .65, p < .05) and SQD-D subscales (r = .47, p < .05). ROC analysis suggested an area of .951 (95% CI = .917–.985) for the PTSD prediction. Basing on sensibility (.963) and specificity (.189), the best cut-off of 2.0 allowed discriminating for PTSD positive cases. After 20 months of the earthquake, the estimate prevalence of PTSD among the survivors is of 21.71% with a consistent and graded association between exposure variables and vulnerability factors (gender, age, exposure to death and home damage) and PTSD symptoms.

scholarly journals SKALA KARAKTER WIRAUSAHA (SK-WIRA): KONSTRUKSI DAN VALIDASI AWAL

2019 ◽  
Vol 17 (2) ◽  
pp. 143
Author(s):  
Aftina Nurul Husna ◽  
Aning Az Zahra ◽  
A Amrul Haq
Keyword(s):  
Factor Analysis ◽  
Achievement Motivation ◽  
Phase 1 ◽  
Model Fit ◽  
Entrepreneurial Activity ◽  
Confirmatory Factor ◽  
Good Internal Consistency ◽  
Preliminary Study ◽  
Correlated Factors ◽  
Item Types

This article reports development of new scale to measure entrepreneurial characters. Entrepreneurial Characters Scale (SK-WIRA) measures personality traits indicating a person’s capacity to engage in entrepreneurial activity and can be used to study tendency and suitability to work as entrepreneur. In preliminary study, entrepreneurial character is operationalized based on concepts found in literatures: achievement motivation, innovativeness, risk taking, and autonomy. Four SK-WIRA subscales were constructed according to those dimensions. In phase 1 item selection, exploratory factor analysis and reliability analysis were applied. Initial set of SK-WIRA constituted of 40-48 items per subscale was administered to university students (N = 130). It is found that items were not clustered based on the theory, but item types (favorable-unfavorable). Therefore, it is predicted that entrepreneurial characters and non-entrepreneurial characters are probably two different constructs and need to be measured using different tools. Final compilation of SK-WIRA consists only 22 items (all is favorable items) with good internal consistency (Cronbach’s α = .863). Phase 2 construct validity test using confirmatory factor analysis (CFA) confirms that SK-WIRA consists of four correlated factors. The examination of scale internal structure shows good model fit (c2/df = 244.077/205; RMSEA = .038; CFI = .943; TLI = .936; SRMR = .069).

scholarly journals O009 The Good Sleeper Scale-13 Items: a standardised questionnaire for the assessment of good sleepers

2021 ◽  
Vol 2 (Supplement_1) ◽  
pp. A4-A5
Author(s):  
J Manners ◽  
S Appleton ◽  
A Reynolds ◽  
Y Melaku ◽  
T Gill ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Online Survey ◽  
Secondary Analysis ◽  
Model Fit ◽  
Sleep Health ◽  
Daytime Functioning ◽  
Confirmatory Factor ◽  
Health Rating ◽  
Future Work ◽  
Good Sleep

Abstract Introduction Good sleep is not merely the absence of sleep disorder symptoms, yet this criterion is commonly applied in research studies. We developed the Good Sleeper Scale-13 (GSS-13) to standardise identification of good sleepers. Methods We conducted a secondary analysis of the 2019 Sleep Health Foundation online survey of adult Australians (N = 2,044, aged 18–90 years). Possible GSS-13 items were chosen collaboratively with co-authors. Exploratory factor analysis (EFA) was conducted on 10% of the dataset chosen at random (N = 191) for factor identification and item reduction. Confirmatory factor analysis (CFA) on the remaining 90% (N = 1,853) tested model fit. Associations with sleep concerns, health, and daytime functioning tested validity of the final version. Results From EFA, six factors were identified: Adequate Sleep; Insomnia; Regularity; Timing; Sleep Duration; Perceived Sleep Problem. On CFA, model fit was comparable to other sleep instruments, X² (67) = 387.34, p &lt; .001, CFI = .95, TLI = .92, RMSEA = .05. Cronbach’s alpha was largely acceptable (≥.7) across subscales. Consistent correlations were found between GSS-13 global scores and outcomes, including “a good night’s sleep” (r = .65, p &lt; .001), feeling un-refreshed (r = -.53, p &lt; .001), and general health rating (r = .44, p &lt; .001). Classification accuracy for insomnia symptoms was also high (AUC = .84). Conclusions The GSS-13 is psychometrically sound, correlated well with sleep, health, and daytime functioning, and can be used to identify good sleepers for research. Future work will test relationships with other sleep measures.

Factorial Structure of the Therapist Adherence Measure-Revised (TAM-R) Within Multisystemic Therapy

2020 ◽  
Vol 36 (2) ◽  
pp. 427-431
Author(s):  
Aurelie M. C. Lange ◽  
Marc J. M. H. Delsing ◽  
Ron H. J. Scholte ◽  
Rachel E. A. van der Rijken
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Multisystemic Therapy ◽  
Model Fit ◽  
Validity And Reliability ◽  
Adherence Measure ◽  
Therapist Adherence ◽  
Confirmatory Factor ◽  
The Us

Abstract. The Therapist Adherence Measure (TAM-R) is a central assessment within the quality-assurance system of Multisystemic Therapy (MST). Studies into the validity and reliability of the TAM in the US have found varying numbers of latent factors. The current study aimed to reexamine its factor structure using two independent samples of families participating in MST in the Netherlands. The factor structure was explored using an Exploratory Factor Analysis (EFA) in Sample 1 ( N = 580). This resulted in a two-factor solution. The factors were labeled “therapist adherence” and “client–therapist alliance.” Four cross-loading items were dropped. Reliability of the resulting factors was good. This two-factor model showed good model fit in a subsequent Confirmatory Factor Analysis (CFA) in Sample 2 ( N = 723). The current finding of an alliance component corroborates previous studies and fits with the focus of the MST treatment model on creating engagement.

Probability-Based and Measurement-Related Hypotheses With Full Restriction for Investigations by Means of Confirmatory Factor Analysis

Methodology ◽  
2011 ◽  
Vol 7 (4) ◽  
pp. 157-164
Author(s):  
Karl Schweizer
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Processing ◽  
Latent Variables ◽  
Repeated Measures ◽  
Latent Variable ◽  
Model Fit ◽  
Repeated Measures Data ◽  
Confirmatory Factor ◽  
And Performance

Probability-based and measurement-related hypotheses for confirmatory factor analysis of repeated-measures data are investigated. Such hypotheses comprise precise assumptions concerning the relationships among the true components associated with the levels of the design or the items of the measure. Measurement-related hypotheses concentrate on the assumed processes, as, for example, transformation and memory processes, and represent treatment-dependent differences in processing. In contrast, probability-based hypotheses provide the opportunity to consider probabilities as outcome predictions that summarize the effects of various influences. The prediction of performance guided by inexact cues serves as an example. In the empirical part of this paper probability-based and measurement-related hypotheses are applied to working-memory data. Latent variables according to both hypotheses contribute to a good model fit. The best model fit is achieved for the model including latent variables that represented serial cognitive processing and performance according to inexact cues in combination with a latent variable for subsidiary processes.

scholarly journals Genes and hormones of the hypothalamic–pituitary–adrenal axis in post-traumatic stress disorder. What is their role in symptom expression and treatment response?

2021 ◽  
Author(s):  
Susanne Fischer ◽  
Tabea Schumacher ◽  
Christine Knaevelsrud ◽  
Ulrike Ehlert ◽  
Sarah Schumacher
Keyword(s):  
Hpa Axis ◽  
Post Traumatic Stress Disorder ◽  
Traumatic Stress ◽  
Stress Disorder ◽  
Ptsd Symptoms ◽  
Post Traumatic Stress ◽  
Alternative Treatments ◽  
Hypothalamic Pituitary Adrenal ◽  
Post Traumatic

Abstract Background Less than half of all individuals with post-traumatic stress disorder (PTSD) remit spontaneously and a large proportion of those seeking treatment do not respond sufficiently. This suggests that there may be subgroups of individuals who are in need of augmentative or alternative treatments. One of the most frequent pathophysiological findings in PTSD is alterations in the hypothalamic–pituitary–adrenal (HPA) axis, including enhanced negative feedback sensitivity and attenuated peripheral cortisol. Given the role of the HPA axis in cognition, this pattern may contribute to PTSD symptoms and interfere with key processes of standard first-line treatments, such as trauma-focused cognitive behavioural therapy (TF-CBT). Methods This review provides a comprehensive summary of the current state of research regarding the role of HPA axis functioning in PTSD symptoms and treatment. Results Overall, there is preliminary evidence that hypocortisolaemia contributes to symptom manifestation in PTSD; that it predicts non-responses to TF-CBT; and that it is subject to change in parallel with positive treatment trajectories. Moreover, there is evidence that genetic and epigenetic alterations within the genes NR3C1 and FKBP5 are associated with this hypocortisolaemic pattern and that some of these alterations change as symptoms improve over the course of treatment. Conclusions Future research priorities include investigations into the role of the HPA axis in day-to-day symptom variation, the time scale in which biological changes in response to treatment occur, and the effects of sex. Furthermore, before conceiving augmentative or alternative treatments that target the described mechanisms, multilevel studies are warranted.

A Comparison of Reliability Estimation Based on Confirmatory Factor Analysis and Exploratory Structural Equation Models

2021 ◽  
pp. 001316442110089
Author(s):  
Yuanshu Fu ◽  
Zhonglin Wen ◽  
Yang Wang
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Structural Equation ◽  
Reliability Estimation ◽  
Model Fit ◽  
Equation Modeling ◽  
Factor Loadings ◽  
Reliability Estimates ◽  
Confirmatory Factor ◽  
Composite Reliability

Composite reliability, or coefficient omega, can be estimated using structural equation modeling. Composite reliability is usually estimated under the basic independent clusters model of confirmatory factor analysis (ICM-CFA). However, due to the existence of cross-loadings, the model fit of the exploratory structural equation model (ESEM) is often found to be substantially better than that of ICM-CFA. The present study first illustrated the method used to estimate composite reliability under ESEM and then compared the difference between ESEM and ICM-CFA in terms of composite reliability estimation under various indicators per factor, target factor loadings, cross-loadings, and sample sizes. The results showed no apparent difference in using ESEM or ICM-CFA for estimating composite reliability, and the rotation type did not affect the composite reliability estimates generated by ESEM. An empirical example was given as further proof of the results of the simulation studies. Based on the present study, we suggest that if the model fit of ESEM (regardless of the utilized rotation criteria) is acceptable but that of ICM-CFA is not, the composite reliability estimates based on the above two models should be similar. If the target factor loadings are relatively small, researchers should increase the number of indicators per factor or increase the sample size.

Development of the Adherence to Healthy Behaviors Scale

2021 ◽  
pp. 105477382098862
Author(s):  
Chen-Hui Huang ◽  
Dhea Natashia ◽  
Tzu-Chia Lin ◽  
Miaofen Yen
Keyword(s):  
Factor Analysis ◽  
Protective Factor ◽  
Model Fit ◽  
Convenience Sample ◽  
Healthy Behaviors ◽  
Confirmatory Factor ◽  
Reliable Instrument ◽  
Principal Axis Factor Analysis ◽  
Southern Taiwan ◽  
Test Retest Reliability

Adherence to healthy behaviors is a protective factor in the disease progression of chronic kidney disease (CKD). Measuring adherence can lead to the recognition of unhealthy behaviors and the suggestion of programs to prevent poor health outcomes. An assessment measurement for patients with CKD not requiring dialysis was developed and psychometrically tested. A convenience sample ( n = 330) of patients with CKD attending a nephrology clinic in southern Taiwan completed the 13-item Adherence to Healthy Behaviors Scale (AHBS). A principal axis factor analysis and a parallel analysis demonstrated a three-factor structure accounting for 47.16% of the total variance. Confirmatory factor analysis indicated a good model fit. The criterion-related validity was adequate ( r = .51; p < .000), with a Cronbach’s alpha of .70; the test-retest reliability demonstrated good stability ( r = .70; p < .000). The AHBS is a valid, reliable instrument to assess adherence to healthy behaviors among patients with CKD.

Do We Share the Same View? Validating the Shared Mental Models in Team Sports Questionnaire

2021 ◽  
Vol 128 (2) ◽  
pp. 831-850
Author(s):  
Charlotte Raue ◽  
Dennis Dreiskaemper ◽  
Bernd Strauss
Keyword(s):  
Mental Models ◽  
Team Sports ◽  
Positive Influence ◽  
Shared Mental Models ◽  
Model Fit ◽  
Sports Performance ◽  
Measurement Instruments ◽  
Team Members ◽  
Confirmatory Factor ◽  
Good Internal Consistency

Shared mental models (SMMs) can exert a positive influence on team sports performance because team members with SMMs share similar tasks and team-related knowledge. There is currently insufficient sports research on SMMs because the underlying theory has not been adapted adequately to the sports context, and different SMMs measurement instruments have been used in past studies. In the present study we aimed to externally validate and determine the construct validity of the “Shared Mental Models in Team Sports Questionnaire” (SMMTSQ). Moreover, we critically examined the theoretical foundation for this instrument. Participants were 476 active team athletes from various sports. While confirmatory factor analysis did not support the SMMTSQ’s hierarchical model, its 13 subfactors showed a good model fit in an explorative correlative approach, and the model showed good internal consistency and item–total correlations. Thus, the instrument’s subfactors can be applied individually, even while there are remaining questions as to whether other questionnaires of this kind are an appropriate means of measuring SMMs in sport.

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