scholarly journals Three-Factor Structure of the eHealth Literacy Scale Among Magnetic Resonance Imaging and Computed Tomography Outpatients: A Confirmatory Factor Analysis

2018 ◽  
Vol 5 (1) ◽  
pp. e6 ◽  
Author(s):  
Lisa L Hyde ◽  
Allison W Boyes ◽  
Tiffany-Jane Evans ◽  
Lisa J Mackenzie ◽  
Rob Sanson-Fisher
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Factor Analysis ◽  
Magnetic Resonance ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Resonance Imaging ◽  
Ehealth Literacy ◽  
Confirmatory Factor ◽  
Three Factor

scholarly journals Three-Factor Structure of the eHealth Literacy Scale Among Magnetic Resonance Imaging and Computed Tomography Outpatients: A Confirmatory Factor Analysis (Preprint)

2017 ◽  
Author(s):  
Lisa L Hyde ◽  
Allison W Boyes ◽  
Tiffany-Jane Evans ◽  
Lisa J Mackenzie ◽  
Rob Sanson-Fisher
Keyword(s):  
Magnetic Resonance Imaging ◽  
Computed Tomography ◽  
Magnetic Resonance ◽  
Factor Structure ◽  
Goodness Of Fit ◽  
Factor Model ◽  
Mean Square ◽  
Resonance Imaging ◽  
Ehealth Literacy ◽  
Three Factor

BACKGROUND Electronic health (eHealth) literacy is needed to effectively engage with Web-based health resources. The 8-item eHealth literacy scale (eHEALS) is a commonly used self-report measure of eHealth literacy. Accumulated evidence has suggested that the eHEALS is unidimensional. However, a recent study by Sudbury-Riley and colleagues suggested that a theoretically-informed three-factor model fit better than a one-factor model. The 3 factors identified were awareness (2 items), skills (3 items), and evaluate (3 items). It is important to determine whether these findings can be replicated in other populations. OBJECTIVE The aim of this cross-sectional study was to verify the three-factor eHEALS structure among magnetic resonance imaging (MRI) and computed tomography (CT) medical imaging outpatients. METHODS MRI and CT outpatients were recruited consecutively in the waiting room of one major public hospital. Participants self-completed a touchscreen computer survey, assessing their sociodemographic, scan, and internet use characteristics. The eHEALS was administered to internet users, and the three-factor structure was tested using structural equation modeling. RESULTS Of 405 invited patients, 87.4% (354/405) were interested in participating in the study, and of these, 75.7% (268/354) were eligible. Of the eligible participants, 95.5% (256/268) completed all eHEALS items. Factor loadings were 0.80 to 0.94 and statistically significant (P<.001). All reliability measures were acceptable (indicator reliability: awareness=.71-.89, skills=.78-.80, evaluate=.64-.79; composite reliability: awareness=.89, skills=.92, evaluate=.89; variance extracted estimates: awareness=.80, skills=.79, evaluate=.72). Two out of three goodness-of-fit indices were adequate (standardized root mean square residual (SRMR)=.038; comparative fit index (CFI)=.944; root mean square error of approximation (RMSEA)=.156). Item 3 was removed because of its significant correlation with item 2 (Lagrange multiplier [LM] estimate 104.02; P<.001) and high loading on 2 factors (LM estimate 91.11; P<.001). All 3 indices of the resulting 7-item model indicated goodness of fit (χ211=11.3; SRMR=.013; CFI=.999; RMSEA=.011). CONCLUSIONS The three-factor eHEALS structure was supported in this sample of MRI and CT medical imaging outpatients. Although further factorial validation studies are needed, these 3 scale factors may be used to identify individuals who could benefit from interventions to improve eHealth literacy awareness, skill, and evaluation competencies.

Psychometric Properties of a Portuguese Version of the Revised Sociosexual Orientation Inventory

2016 ◽  
Vol 7 ◽  
Author(s):  
Félix Neto
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Psychometric Properties ◽  
Factor Structure ◽  
Internal Consistency ◽  
Sociosexual Orientation ◽  
Portuguese Version ◽  
Confirmatory Factor ◽  
Adequate Internal Consistency ◽  
Three Factor

Sociosexuality refers to the propensity to engage in sexual relations without closeness or commitment, varying from a restricted to an unrestricted orientation. The aim of this research was to scrutinise the psychometric properties of a Portuguese version of the revised Sociosexual Orientation Inventory (SOI-R; Penke & Asendorpf, 2008). The study included 549 persons (50% women) aged 18–75 years (M = 38.73; SD = 17.77). The psychometric properties of the SOI-R were analysed by means of confirmatory factor analysis, internal consistency, and validity. Confirmatory factor analysis showed the expected three-factor structure of the measure. The SOI-R presented adequate internal consistency. Women were less unrestricted than men in all facets of sociosexuality. This Portuguese version of the SOI-R seems to be reliable and valid for evaluating sociosexuality in a Portuguese-speaking population, and can be utilised for experimental and applied works. The significance and limitations of the results are discussed.

scholarly journals Bayesian confirmatory factor analysis and higher-level scores of interpersonal problems with circumplex structure

2021 ◽  
Author(s):  
Anneke Cleopatra Weide ◽  
Vera Scheuble ◽  
André Beauducel
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Level Structure ◽  
Interpersonal Problems ◽  
Factor Scores ◽  
Correlation Pattern ◽  
Confirmatory Factor ◽  
Three Factor

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than maximum likelihood confirmatory factor analysis. Using a nonclinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores, posterior mean factor scores from Bayesian confirmatory factor analysis, and weighted sum scores. We found excellent reliability (with Rtt ≥ .90) for Dominance, Love, and Distress for all scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlation pattern with external measures – Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism – were in line with theoretical expectations. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

Reasons for Living Inventory: Cross-Cultural Construct Validity

2007 ◽  
Vol 100 (3_suppl) ◽  
pp. 1259-1262 ◽  
Author(s):  
Maurizio Pompili ◽  
Paolo Girardi ◽  
Roberto Tatarelli ◽  
David Lester ◽  
James R. Rogers
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Construct Validity ◽  
Factor Structure ◽  
Cross Cultural ◽  
Reasons For Living ◽  
Confirmatory Factor ◽  
Cultural Construct ◽  
Reasons For Living Inventory ◽  
Three Factor

The construct validity of the Reasons for Living Inventory was explored with a sample of 340 Italian students. The results of confirmatory factor analysis did not support strongly the six-factor structure previously identified. An exploratory factor analysis indicated a three-factor structure, suggesting that researchers should be cautious in assuming the validity of the six-factor structure in cross-cultural settings.

scholarly journals Three-Factor Physical Perfectionism Scale as a New Tool for the Assessment of the Pathogenic Appearance Standards in the Modern Culture

2020 ◽  
Vol 28 (4) ◽  
pp. 98-117
Author(s):  
A.B. Kholmogorova ◽  
A.A. Rakhmanina
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Fit Indices ◽  
Modern Culture ◽  
Gender Invariance ◽  
Symptoms Of Depression ◽  
Confirmatory Factor ◽  
Cultural Standards ◽  
Three Factor

The paper presents a three-factor version of the Physical Perfectionism Scale. The study was conducted on a sample of students living in Moscow (n=125) and Astrakhan (n=75), including 155 women and 45 men (Mage=19,5; SD=1,83). The factor structure of the questionnaire was confirmed by means of confirmatory factor analysis. The model did not pass the test for gender invariance but showed high fit indices regardless of the cultural standards adopted in the place of residence of the respondents. The identified factors were found to be significantly associated with dissatisfaction with one’s appearance, perceived socio-cultural pressure, as well as fear of negative assessment, and the severity of symptoms of depression.

scholarly journals Bayesian and Maximum-Likelihood Modeling and Higher-Level Scores of Interpersonal Problems With Circumplex Structure

2021 ◽  
Vol 12 ◽  
Author(s):  
Anneke C. Weide ◽  
Vera Scheuble ◽  
André Beauducel
Keyword(s):  
Factor Analysis ◽  
Maximum Likelihood ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Clinical Sample ◽  
Level Structure ◽  
Interpersonal Problems ◽  
Online Questionnaire ◽  
Confirmatory Factor ◽  
Three Factor

Difficulties in interpersonal behavior are often measured by the circumplex-based Inventory of Interpersonal Problems. Its eight scales can be represented by a three-factor structure with two circumplex factors, Dominance and Love, and a general problem factor, Distress. Bayesian confirmatory factor analysis is well-suited to evaluate the higher-level structure of interpersonal problems because circumplex loading priors allow for data-driven adjustments and a more flexible investigation of the ideal circumplex pattern than conventional maximum likelihood confirmatory factor analysis. Using a non-clinical sample from an online questionnaire study (N = 822), we replicated the three-factor structure of the IIP by maximum likelihood and Bayesian confirmatory factor analysis and found great proximity of the Bayesian loadings to perfect circumplexity. We found additional support for the validity of the three-factor model of the IIP by including external criteria-Agreeableness, Extraversion, and Neuroticism from the Big Five and subclinical grandiose narcissism-in the analysis. We also investigated higher-level scores for Dominance, Love, and Distress using traditional regression factor scores and weighted sum scores. We found excellent reliability (with Rtt ≥ 0.90) for Dominance, Love, and Distress for the two scoring methods. We found high congruence of the higher-level scores with the underlying factors and good circumplex properties of the scoring models. The correlational pattern with the external measures was in line with theoretical expectations and similar to the results from the factor analysis. We encourage the use of Bayesian modeling when dealing with circumplex structure and recommend the use of higher-level scores for interpersonal problems as parsimonious, reliable, and valid measures.

Assessing professionals' adoption readiness for eMental Health: Development and Validation of the eMental Health Adoption Readiness (eMHAR) Scale (Preprint)

2021 ◽  
Author(s):  
Milou Feijt ◽  
Yvonne de Kort ◽  
Joyce Westerink ◽  
Joyce Bierbooms ◽  
Inge Bongers ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Confirmatory Factor Analysis ◽  
Factor Structure ◽  
Internal Consistency ◽  
Healthcare Professionals ◽  
Mental Healthcare ◽  
Factor Analyses ◽  
Confirmatory Factor ◽  
Exploratory Factor Analyses ◽  
Three Factor

BACKGROUND Over the last decades, significant advances have been made in the development of digital tools and applications for mental healthcare. Yet, despite growing evidence for their effectiveness, their acceptance and use in clinical practice remain low. To gain further insights in the process of eMental Health adoption and to facilitate future research on this topic, a validated and easy-to-use instrument to assess professionals' readiness to adopt eMental Health is necessary. OBJECTIVE The aim of this study was to develop and validate an instrument for assessing mental healthcare professionals' adoption readiness for eMental Health. METHODS Item generation was guided by literature and input from mental healthcare professionals and experts in survey development. Exploratory factor analyses were conducted on an initial set of 29 items completed by a sample of mental healthcare professionals (N = 432), after which the scale was reduced to 15 items in an iterative process. The factor structure thus obtained was subsequently tested with a confirmatory factor analysis with a second sample of mental healthcare professionals (N = 363). Internal consistency, convergent validity and predictive validity of the eMHAR Scale were assessed. RESULTS Exploratory factor analyses resulted in a three-factor solution with 15 items. The factors were analyzed and labeled as ‘perceived benefits and applicability of EMH’, ‘EMH proactive innovation’, and ‘EMH self-efficacy’. These factors were confirmed through a confirmatory factor analysis. The total scale and subscales showed good internal consistency (Cronbach’s alpha = 0.73-0.88) and acceptable convergent and predictive relations to related constructs. CONCLUSIONS The constructed eMHAR Scale showed a conceptually interpretable three-factor structure with satisfactory characteristics and relationships with relevant concepts. Its ease of use allows for a quick acquisition of data that can contribute to understanding and facilitating the process of adoption of eMental Health by clinical professionals.

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