scholarly journals Empirical Approach to Developing an Optimal Socioeconomic Status Index for Health Surveillance

2022 ◽  
Author(s):  
Jordana LaFantasie ◽  
Francis Boscoe
Keyword(s):  
Socioeconomic Status ◽  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Health Surveillance ◽  
Cancer Surveillance ◽  
Income Poverty ◽  
One Dimensional ◽  
Indicator Variables ◽  
Statistical Consistency

The association between multi-dimensional deprivation and public health is well established, and many area-based indices have been developed to measure or account for socioeconomic status in health surveillance. The Yost Index, developed in 2001, has been adopted in the US for cancer surveillance and is based on the combination of two heavily weighted (household income, poverty) and five lightly weighted (rent, home value, employment, education and working class) indicator variables. Our objectives were to 1) update indicators and find a more parsimonious version of the Yost Index by examining potential models that included indicators with more balanced weights/influence and reduced redundancy and 2) test the statistical consistency of the factor upon which the Yost Index is based. Despite the usefulness of the Yost Index, a one-factor structure including all seven Yost indicator variables is not statistically reliable and should be replaced with a three-factor model to include the true variability of all seven indicator variables. To find a one-dimensional alternative, we conducted maximum likelihood exploratory factor analysis on a subset of all possible combinations of fourteen indicator variables to find well-fitted one-dimensional factor models and completed confirmatory factor analysis on the resulting models. One indicator combination (poverty, education, employment, public assistance) emerged as the most stable unidimensional model. This model is more robust to extremes in local cost of living conditions, is comprised of ACS variables that rarely require imputation by the end-user and is a more parsimonious solution than the Yost index with a true one-factor structure.

scholarly journals Driving locus of control: The Czech adaptation

2021 ◽  
Vol 65 (1) ◽  
pp. 86-100
Author(s):  
Vít Gabrhel ◽  
◽  
Stanislav Ježek ◽  
Petr Zámečník
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Structural Equation Modelling ◽  
Structural Equation ◽  
Factor Model ◽  
One Dimensional ◽  
Equation Modelling ◽  
Confirmatory Factor ◽  
The One

Objectives. This study attempts to introduce the Driving Locus of Control (DLoC), a method focused on the internal or external source of attribution of the driving behaviour, to the Czech context. This study also relates DLoC to attitudes towards autonomous vehicles (AVs). Participants and setting. Out of the general population, 59 inquirers personally interviewed (CAPI) 1 065 respondents (49% women) in the age range between 15 and 92 years (M = 50, SD = 17). The respondents were sampled via multistage random sampling procedure, based on the list of addresses in the Czech Republic. Hypotheses. The authors hypothesised to replicate the original two-factor structure of the DLoC Scale and that the higher levels of internal DLoC result in not considering the improvement in traffic safety as the AVs replace human drivers. Statistical analysis. Confirmatory factor analysis was used to analyse the factor structure of DLoC Scale. Hypotheses related to the empirical validity of the method were assessed via structural equation modelling. The reliability of DLoC Scale was calculated in terms of internal consistency (McDonald coefficient). Results. Confirmatory factor analysis revealed reasonably good support for structural validity of the one-dimensional DLoC-CZ15 factor model (χ2 = 426.967, df = 90, CFI = 0.964, TLI = 0.958, SRMR = 0.066, RMSEA = 0.065). In addition, the one-dimensional DLoC-CZ15 factor model showed acceptable internal consistency - ω = 0.9 (95% CI [0.89, 0.91]). The structural equation modelling found a relationship between DLoC and some of the items capturing attitudes towards AVs, too. Study limitations. The analysed data were obtained via interviews between respondents and inquirers. As a result, the study does not contain indicators of empirical validity measured by a methodologically different approach, such as an observation of driving behaviour.

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.

An investigation into the factor structure of the Cognitive Therapy Scale – Revised (CTS-R) in a CBT training sample

2021 ◽  
pp. 1-11
Author(s):  
Sarah Beale ◽  
Silia Vitoratou ◽  
Sheena Liness
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Cognitive Therapy ◽  
Exploratory Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Single Factor ◽  
Behaviour Therapy ◽  
Cognitive Behaviour ◽  
Confirmatory Factor

Abstract Background: Effective monitoring of cognitive behaviour therapy (CBT) competence depends on psychometrically robust assessment methods. While the UK Cognitive Therapy Scale – Revised (CTS-R; Blackburn et al., 2001) has become a widely used competence measure in CBT training, practice and research, its underlying factor structure has never been investigated. Aims: This study aimed to present the first investigation into the factor structure of the CTS-R based on a large sample of postgraduate CBT trainee recordings. Method: Trainees (n = 382) provided 746 mid-treatment audio recordings for depression (n = 373) and anxiety (n = 373) cases scored on the CTS-R by expert markers. Tapes were split into two equal samples counterbalanced by diagnosis and with one tape per trainee. Exploratory factor analysis was conducted. The suggested factor structure and a widely used theoretical two-factor model were tested with confirmatory factor analysis. Measurement invariance was assessed by diagnostic group (depression versus anxiety). Results: Exploratory factor analysis suggested a single-factor solution (98.68% explained variance), which was supported by confirmatory factor analysis. All 12 CTS-R items were found to contribute to this single factor. The univariate model demonstrated full metric invariance and partial scalar invariance by diagnosis, with one item (item 10 – Conceptual Integration) demonstrating scalar non-invariance. Conclusions: Findings indicate that the CTS-R is a robust homogenous measure and do not support division into the widely used theoretical generic versus CBT-specific competency subscales. Investigation into the CTS-R factor structure in other populations is warranted.

Exploring the Factor Structure of the Job Demands-Resources Measure With Patient Violence on Direct Care Workers in the Home Setting

2017 ◽  
Vol 25 (2) ◽  
pp. 257-274 ◽  
Author(s):  
Ha Do Byon ◽  
Donna Harrington ◽  
Carla L. Storr ◽  
Jane Lipscomb
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Job Demands ◽  
Direct Care ◽  
Direct Care Workers ◽  
Home Setting ◽  
Patient Violence ◽  
Measurement Framework ◽  
Care Workers

Background and Purpose: Workplace violence research in health care settings using the Job Demands-Resources (JD-R) framework is hindered by the lack of comprehensive examination of the factor structure of the JD-R measure when it includes patient violence. Is patient violence a component of job demands or its own factor as an occupational outcome? Method: Exploratory factor analysis and confirmatory factor analysis were conducted using a sample of direct care workers in the home setting (n = 961). Results: The overall 2-construct JD-R structure persisted. Patient violence was not identified as a separate factor from job demands; rather, two demand factors emerged: violence/emotional and workload/physical demands. Conclusions: Although the three-factor model fits the data, the two-factor model with patient violence being a component of job demands is a parsimonious and effective measurement framework.

scholarly journals Evaluation of the Factor Structure of the Adolescent Stress Questionnaire in Chinese Adolescents

2018 ◽  
Vol 122 (6) ◽  
pp. 2366-2395
Author(s):  
Tianpeng Ye ◽  
Naixue Cui ◽  
Wen Yang ◽  
Jianghong Liu
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Behavioral Problems ◽  
Romantic Relationship ◽  
Factor Model ◽  
Chinese Adolescents ◽  
School Students ◽  
Cross Cultural Differences ◽  
Distinct Factor ◽  
Adolescent Stress

This study evaluated the psychometric properties of the Chinese version of Adolescent Stress Questionnaire ( ASQ-CN) in a sample of Chinese middle school students ( N = 420; 52.14% boys and 47.86% girls). Iterated principal factor analysis and multiple-group principal components cluster analysis supported a six-factor model with 42 items out of 58 items in the ASQ-CN. The internal consistency was from .82 to .90. Girls reported lower stress levels in one subscale, Stress of romantic relationship, whereas no gender differences were found in the other five subscales. Compared with other studies of the ASQ in Westernized countries, the ASQ-CN showed a distinct factor structure that may be explained by cross-cultural differences. Scales constructed from factor analysis related negatively to measures of mindfulness and positively to a measure of behavioral problems, suggesting that they were valid for Chinese adolescent stress. The study did not support a higher order construct of the ASQ-CN. Altogether, our findings suggest that the ASQ-CN is adequate for assessing stressors in Chinese adolescents.

scholarly journals Factor Structure and Gender Invariance Testing for the Sport Anxiety Scale-2 (SAS-2)

2018 ◽  
Vol 12 (2) ◽  
pp. 201-217
Author(s):  
Leilani A. Madrigal ◽  
Vincenzo Roma ◽  
Todd Caze ◽  
Arthur Maerlender ◽  
Debra Hope
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Online Survey ◽  
Factor Model ◽  
Anxiety Scale ◽  
Negative Evaluation ◽  
Psychometric Validation ◽  
Confirmatory Factor Analyses ◽  
Analysis Group ◽  
Confirmatory Factor

This study aimed to provide further psychometric validation of the Sport Anxiety Scale-2 (SAS-2) by assessing the factor structure, invariance across gender, and convergent and divergent validity of the SAS-2 by correlating both related (i.e., anxiety sensitivity, brief fear of negative evaluation, intolerance of uncertainty, and negative affect) and unrelated constructs (i.e., positive affect, self-confidence). A total of 542 current and former competitive athletes completed a questionnaire through Amazon’s Mechanical Turk system. All data were collected via online survey. Participants were randomly assigned to an exploratory factor analysis (n = 271) and confirmatory factor analysis group (n = 271). Results indicated that both exploratory and confirmatory factor analyses supported the three-factor model of anxiety involving somatic anxiety, worry, and concentration disruption. Additionally, this study found the SAS-2 to be reliable, gender invariant, and have strong construct validity. Our findings extend the generalizability of the SAS-2 in more varied populations of athletic backgrounds.

Cross-Cultural Validation of the Modified Practice Attitudes Scale: Initial Factor Analysis and a New Factor Model

Assessment ◽  
2016 ◽  
Vol 25 (1) ◽  
pp. 126-138 ◽  
Author(s):  
Heehoon Park ◽  
Chad K. Ebesutani ◽  
Kyong-Mee Chung ◽  
Cameo Stanick
Keyword(s):  
Mental Health ◽  
Factor Analysis ◽  
Health System ◽  
Factor Structure ◽  
Mental Health System ◽  
Service Providers ◽  
Factor Model ◽  
Reliability And Validity ◽  
Significant Group ◽  
The One

Objective: The objective of this study was to create the Korean version of the Modified Practice Attitudes Scale (K-MPAS) to measure clinicians’ attitudes toward evidence-based treatments (EBTs) in the Korean mental health system. Method: Using 189 U.S. therapists and 283 members from the Korean mental health system, we examined the reliability and validity of the MPAS scores. We also conducted the first exploratory and confirmatory factor analysis on the MPAS and compared EBT attitudes across U.S. and Korean therapists. Results: Results revealed that the inclusion of both “reversed-worded” and “non–reversed-worded” items introduced significant method effects that compromised the integrity of the one-factor MPAS model. Problems with the one-factor structure were resolved by eliminating the “non–reversed-worded” items. Reliability and validity were adequate among both Korean and U.S. therapists. Korean therapists also reported significantly more negative attitudes toward EBTs on the MPAS than U.S. therapists. Conclusions: The K-MPAS is the first questionnaire designed to measure Korean service providers’ attitudes toward EBTs to help advance the dissemination of EBTs in Korea. The current study also demonstrated the negative impacts that can be introduced by incorporating oppositely worded items into a scale, particularly with respect to factor structure and detecting significant group differences.

scholarly journals The Connor-Davidson Resilience Scale in Critical Care Nurses: A Psychometric Analysis

2016 ◽  
Vol 24 (1) ◽  
pp. 28-39 ◽  
Author(s):  
Meredith Mealer ◽  
Sarah J. Schmiege ◽  
Paula Meek
Keyword(s):  
Factor Analysis ◽  
Critical Care ◽  
Factor Structure ◽  
Model Comparison ◽  
Factor Model ◽  
The United States ◽  
Critical Care Nurses ◽  
Group Differences ◽  
Resilience Scale ◽  
Confirmatory Factor

Objective: (a) To investigate the factor structure of the Connor-Davidson Resilience Scale (CD-RISC) in critical care nurses, using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) and (b) to assess reliability and known group differences of the CD-RISC on critical care nurses. Methods: CD-RISC surveys were collected on 744 critical care nurses across the United States. An abridged version of the CD-RISC was used for the EFA and CFA. Further reliability and known group differences were also tested. Results: EFA identified 3 factors with eigenvalues >1.0 and an explained variance of 59%. The factors were labeled personal competence, perseverance, and leadership, and each factor had salient loadings. The 3-factor CFA provided good fit to the data, χ2 = 243.1, p < .001; RMSEA = .062; CFI = .935, although correlations among the 3 factors were high (.78–.86). A 1-factor model was subsequently tested but did not produce a better fit, and model comparison analyses supported retention of the 3-factor model. Known group differences was supported as intensive care unit (ICU) nurses with a diagnosis of posttraumatic stress disorder (PTSD) had significantly lower total resilience scores (M = 75.43) compared to those without a diagnosis of PTSD (M = 83.21; t = 5.01; p < .001). Discussion: The current investigation found that the 3-factor structure provided the best fit for the data on the abridged version of the CD-RISC in a population of ICU nurses. Analyses also supported the reliability and known group differences of the 16-item measure. Further research is needed to examine trait and capacity features of resilience as it relates to this population.

Factor Structure of the Research Training Environment Scale-Revised:

1997 ◽  
Vol 25 (1) ◽  
pp. 22-37 ◽  
Author(s):  
Jeffrey H. Kahn ◽  
Charles J. Gelso
Keyword(s):  
Factor Analysis ◽  
Factor Structure ◽  
Factor Model ◽  
Research Training ◽  
Second Order ◽  
Training Environment ◽  
Environment Scale ◽  
Order Factor ◽  
Research Training Environment ◽  
Interpersonal Dimension

The factor structure of the Research Training Environment Scale-Revised was examined in a sample of 270 graduate students in counseling psychology. This confirmatory factor analysis assessed the fit of a nine-factor model corresponding to the respective subscales on the measure, as well as the fit of a second-order factor structure suggested by an exploratory factor analysis of data. The second-order factor structure fit very well when conducted on manifest (i.e., observed) subscale total scores; the results were more ambiguous when first-order latent factors were included in the factor structure. The analyses suggested that an instructional dimension and an interpersonal dimension are global factors of the research training environment.

Confirmatory Factor Analysis of Dospert Scale with Chinese University Students

2014 ◽  
Vol 114 (1) ◽  
pp. 185-197 ◽  
Author(s):  
Joseph Wu ◽  
Hoi Yan Cheung
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Undergraduate Students ◽  
Risk Taking ◽  
Factor Model ◽  
Empirical Support ◽  
Convenience Sample ◽  
Domain Specific ◽  
Confirmatory Factor

The factor structure of the 30-item Domain Specific Risk Taking Attitude (DOSPERT) scale (Blais & Weber, 2006) was examined with a convenience sample of 205 Chinese undergraduate students from Macao. A comparison of five competing models via confirmatory factor analysis yielded empirical support for the perspective that risk-taking attitude was content-dependent. After removing the items in the Financial subscale of the DOSPERT scale and some post hoc modifications, a reasonably good fit to the four-correlated-factor model was achieved, in concordance with the theoretical framework. However, items in some scales needed further revision to purify their factor structure so that the DOSPERT scale would be a more psychometrically sound measure for investigating one's risk-taking attitudes in different life domains.

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