Item Covariance Research Articles

Item-Explanatory Mokken Scale Analysis: Using Nonparametric Item Response Theory to Explore Item Attributes

Researchers frequently examine the effects of item attributes (i.e., item properties, item covariates, item formats) as part of item analysis for cognitive and affective assessments. In this study, we propose and illustrate item-explanatory Mokken Scale Analysis (MSA) as an exploratory nonparametric approach to examining item attributes based on invariance principles. We used real data and an illustrative simulation to demonstrate the approach under various conditions. Our results suggest that item-explanatory MSA provides practical and theoretical insight to support measurement research in a variety of contexts. Because of the emphasis on invariance, our approach can help researchers explore the impact of item characteristics on examinee responses and evaluate the degree to which item characteristics have a consistent interpretation for all examinees. We consider the implications of our findings for research and practice, along with directions for further investigation.

Understanding Ability and Reliability Differences Measured with Count Items: The Distributional Regression Test Model and the Count Latent Regression Model

In psychology and education, tests (e.g., reading tests) and self-reports (e.g., clinical questionnaires) generate counts, but corresponding Item Response Theory (IRT) methods are underdeveloped compared to binary data. Recent advances include the Two-Parameter Conway-Maxwell-Poisson model (2PCMPM), generalizing Rasch’s Poisson Counts Model, with item-specific difficulty, discrimination, and dispersion parameters. Explaining differences in model parameters informs item construction and selection but has received little attention. We introduce two 2PCMPM-based explanatory count IRT models: The Distributional Regression Test Model for item covariates, and the Count Latent Regression Model for (categorical) person covariates. Estimation methods are provided and satisfactory statistical properties are observed in simulations. Two examples illustrate how the models help understand tests and underlying constructs.

Validation and results of a novel survey assessing decisional balance for a whole food plant-based diet among US adults.

ImportanceConsuming a whole food plant-based diet (WFPBD) is a promising, low-risk strategy for reducing risk of prevalent chronic disease and certain cancers, with synergistic benefits for climate and environment. However, few US adults report consuming a WFPBD. Understanding the reasons for this inconsistency is important for developing and implementing interventions for promoting a WFPBD. However, no research to elucidate decisional balance driving current consumption patterns in the US exists.ObjectiveThis research aims to validate an online survey to assess decisional balance for the consumption of a WFPBD, describe attitudes and beliefs toward adopting a WFPBD, and evaluate socio-demographic differences in decisional balance for consuming a WFPBD among a convenience sample of US adults.DesignOnline cross-sectional data collection followed by confirmatory factor analysis (CFA), validation of internal consistency, and examination of invariance across socio-demographic variables. Sensitivity analysis of full vs. truncated survey to predict self-reported dietary patterns and consumption behaviors were evaluated. Results of the survey and significant differences by socio-demographics were assessed.SettingOnline survey based on previous research, created via Qualtrics, and administered through MTurk.ParticipantsA total of 412 US adults, majority female (66%), White (75%), 30–60 years old (54%), ≥ Bachelor’s degree (85%), and earning ≥ $45K (68%).Main outcomes and measuresFactor loadings, covariance of survey items, associations with self-reported dietary pattern and consumption measures, and differences in pros, cons, and decisional balance across socio-demographic variables.ResultsCFA reduced the survey from 49 to 12 items and demonstrated invariance across socio-demographic variables. Pros and cons varied inversely and significantly (cov = –0.59), as expected. Cronbach’s α ’s for subscales in the final, reduced model were high (>0.80). Pros, cons, and decisional balance in both the full and the reduced model were significantly (p < 0.05) associated with self-reported dietary pattern and consumption.Conclusion and relevanceOur analyses indicate the WFPBD Survey is a parsimonious and psychometrically sound instrument for evaluation of decisional balance to consume a WFPBD diet among our sample of US adults. These results may be instrumental for development and deployment of interventions intended to promote consumption of a WFPBD in the US.

Abstract P053: A Confirmatory Factor Analysis Of The Whole Food Plant-based Diet Attitudes And Beliefs Survey

Background: Despite emerging evidence that a whole food plant-based diet (WFPBD) can reduce risk for CVD morbidity and mortality, adoption rates in the US remain low (~4%). Little is known about why this disconnect exists, and understanding this is critical to designing and implementing interventions intended to increase WFPBD consumption in the US. However, no validated survey instruments intended for use in US adults has been tested. Objective: The purpose of this study is to validate the WFPBD survey instrument using confirmatory factor analysis (CFA). Methods: Survey development was based on previous research in Australia and Europe, and items include “pros” and “cons” of consuming a WFPBD using constructs from the Social Cognitive Theory and the Transtheoretical Model. Sixty-four statements (33 “con” and 31 “pro”) were presented with five-item Likert scale answer options (strongly disagree to strongly agree). The WFPBD survey was administered to 412 English speaking adults in the US via MTurk. Summary statistics and CFA were used to describe outcomes and reduce the number of survey items while optimizing explained variance. Examination of item variance and covariance was used to iteratively fit a second order twelve factor model, a first order eight factor model, and a first order six factor model. Results: The mean age of participants was 34.9 years, and the sample was 12% (48) African American, 6% (25) Asian, 6% (25) Hispanic, 1% (5) Other, and 75% (309) White. The majority (85.7% (349)) had at least a Bachelor’s degree, and 33% (136) made &gt;$65K. After adjustment for low factor loadings and high cross loadings, the first order six factor model remained significant ( X 2 = 491.87, p &lt; 0.001). This model resulted in the best fit, as indicated by low RMSEA = 0.051 and SRMR = 0.048. The six factors were split between “cons” (social support, instrumental support, self-efficacy, health), and “pros” (instrumental support, health). The largest factor loadings for the latent variable WFPBD “cons” were “I wouldn't get enough energy or strength.” (0.85) and “I am not confident that I know how to prepare plant-based meals.” (0.81), while for the latent variable WFPBD “pros”, the highest factor loadings were for “Have a better quality of life.“ (0.77) and “Be fit.” (0.77). Attitudes towards animals and environmental concerns were not highly implicated and were excluded from the final model. Conclusion: The 25-item WFPBD survey produced internally consistent measures of the latent variables WFPBD “pros” and WFPBD “cons” in this sample of US adults. The reduced survey can be used to assess attitudes and beliefs towards a WFPBD and results can guide behavioral interventions development to promote adoption of a WFPBD. Results suggest the importance of reducing negative perceptions of a WFPBD related to energy and strength, increasing self-efficacy for preparing plant-based meals, and emphasizing health benefits.

Explanatory Cognitive Diagnostic Modeling Incorporating Response Times

AbstractThis study proposes explanatory cognitive diagnostic model (CDM) jointly incorporating responses and response times (RTs) with the inclusion of item covariates related to both item responses and RTs. The joint modeling of item responses and RTs intends to provide more information for cognitive diagnosis while item covariates can be used to predict item parameters when item calibration is not feasible in diagnostic assessments or item parameter estimation errors could be too large due to small sample sizes for calibration. In addition, the inclusion of the item covariates allows the evaluation of cognitive theories underlying the test design in item development. Model parameter estimation is explored using the Bayesian Markov chain Monte Carlo (MCMC) method. A Monte Carlo simulation study is conducted to examine the parameter recovery of the proposed model under different simulated conditions in comparison to alternative competing models. Further, the application of the proposed model is illustrated using the Programme for International Student Assessment (PISA) 2012 problem‐solving items modeling both item response and RT data. The study results indicate that model parameters can be well recovered using the MCMC algorithm and the explanatory CDM jointly incorporating item responses and RTs with item covariates holds promising applications in digital‐based diagnostic assessments.

Examining the Short Dark Tetrad (SD4) Across Models, Correlates, and Gender.

To date, no studies have examined a range of structural models of the interpersonally aversive traits tapped by the Short Dark Tetrad (SD4; narcissism, Machiavellianism, psychopathy, sadism), in conjunction with their measurement invariance (males vs. females) and how the models each predict external correlates. Using a large sample of young adults (N = 3,975), four latent variable models were compared in terms of fit, measurement invariance, and prediction of intrapersonal and interpersonal functioning. The models tested were as follows: (Model A) confirmatory factor analytic, (Model B) bifactor, (Model C) exploratory structural equation model, and (Model D) a reduced-item confirmatory factor analytic that maximized item information. All models accounted for item covariance with good precision, although differed in incremental fit. Strong invariance held for all models, and each accounted similarly for the external correlates, highlighting differential predictive effects of the SD4 factors. The results provide support for four theoretically distinct but overlapping dark personality domains.

Abstract A009: Validation of an instrument to measure health professionals' health literacy competence

Abstract Introduction: Health literacy (HL) has been identified as a significant predictor of outcomes across the health continuum, including cancer care. As a result it is recommended that all health professionals receive health literacy training. Some institutions have begun integrating health literacy into training programs, but there is a dearth of reliable assessment tools to measure learners' knowledge. Only one validated instrument (Health Literacy Knowledge and Experience Scale (HL-KES)) exists that specifically assess health professionals' health literacy competence, but it was validated for use among nurses. The purpose of this study was to evaluate the reliability and validity of the HL-KES as a suitable measure for assessing the HL knowledge and experience of health promotion professionals. Methods: Advanced (junior and senior) students (n=250) enrolled in bachelor-level health promotion programs in three large public universities in Texas completed the 29-item HL-KES. Exploratory and confirmatory factor analyses were conducted to test the factor structure. Reliability estimates of the overall scale and subscales were assessed using the item covariance method with coefficient alpha (α). Results: The analyses identified three factors that accounted for 62% of the total variance. Twelve items loaded on factor 1 (Knowledge of HL challenges), four items loaded on factor 2 (knowledge of HL assessment strategies), and three items loaded on factor 3 (knowledge of HL principles for written healthcare materials). Results from the test of internal consistency indicated the HL-KES had acceptable reliability for the overall knowledge scale (Cronbach's alpha = 0.77). The sub-scales had Cronbach's alphas ranging from .31 to .52. Conclusion: The results suggest the HLKES is a reliable instrument for assessing health promotion professionals' health literacy knowledge. As a whole, the Cronbach's alpha for the instrument falls within the acceptable range (.65 - .90). The subscales, however, have low reliability coefficients. Cronbach's alpha is a function of test length and inter-item correlation and a couple of subscales had just a few items. Reduction in the number of items no doubt attenuated the internal consistency. Citation Format: Lenna Dawkins-Moultin, Lisako McKyer. Validation of an instrument to measure health professionals' health literacy competence [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr A009.

Validity and invariance according to sex and age of the Paykel Scale of Suicide Ideation in Peruvian adolescents

Introduction: Suicidal ideation is the behavior of the individual linked to irrational thoughts about the life. At present, it is considered as the first step towards suicidal behavior and is mostly associated with teenagers. Method: 251 students between 12 and 18 years old participated (ME = 14.73, SD = 1.57) which responded the Paykel Suicide Scale (PSS) and sociodemographic data. Results: Factor analysis was performed confirmation of 2 unifactorial models, the first model did not present adequate adjustment rates, so which proceeded to the covariance of items 4 and 5, obtaining optimal results in the second model of the one-dimensional instrument. It was subsequently performed a third model of MIMIC invariance, where it was used as predictors to the variables of sex and age to the model previous, which allowed to determine the lack of difference between these categorical groups. Conclusion: It is determined that the PSS is a consistent and reliable test, which yields valid results in the Peruvian population, so you can have an instrument that evaluates suicidal ideation with referential parameters.

The CSS-12: Development and Validation of a Short-Form Version of the Cyberchondria Severity Scale.

Cyberchondria is defined as an increase in anxiety about one's health status as a result of excessive online searches. McElroy and Shevlin (2014) developed the first multidimensional, self-report measure of this construct-the Cyberchondria Severity Scale (CSS). The CSS consists of 33 items which can be summed to form a total score, and/or 5 subscale scores. The aim of the present study was to develop a short-form version of the CSS, removing the "Mistrust" subscale. Participants were undergraduate students from two UK universities (N = 661, 73% female, Mage = 22.19 years, SD = 5.88). Students completed the CSS, Short Health Anxiety Inventory (SHAI) and Generalized Anxiety Disorder Assessment (GAD-7). Twelve items were chosen for retention in the short form based on an exploratory factor analysis. These items corresponded to the four factors previously identified in the 33-item scale (minus the "Mistrust" subscale). Confirmatory factor analysis was used to validate the structure of the CSS-12. Confirmatory bifactor modeling indicated that the majority of item covariance was accounted for by a general cyberchondria factor. Construct validity was assessed by examining associations with the SHAI and GAD-7, with stronger correlations observed between the CSS-12 and the SHAI (compared with the GAD-7). The CSS-12 is a brief, reliable, and valid measure of worry/anxiety attributable to excessive online health research.

An examination of effectiveness of technology push strategies for achieving sustainable development in manufacturing industries

Purpose The purpose of this study is to estimate and extract various significant technology push (TP) strategies influencing sustainable development in Indian manufacturing industries. The study critically examines the effectiveness of TP strategies in manufacturing enterprises. Design/methodology/approach An extensive survey of 92 companies has been executed to identify improvements made by TP strategies to achieve sustainable development in manufacturing industries. The companies in the survey include medium− and large−scale manufacturing enterprises. The correlations between various TP strategies and sustainable development indicators are evaluated and validated using various numerical methods and tools. Findings The focus of the paper is on the distinguishable contributions made by TP strategies such as innovative capability; research and development; corporate strategy; and export orientation toward achieving sustainable development. The inter−relationships between different TP practices with sustainable development indicators have been evaluated to efficiently manage the objectives of growth and sustainability. The research concludes that two TP strategies, namely, corporate strategy and innovative capability, are found to be substantial in the present context. These strategies have emerged as a foundation for several development initiatives and actively support manufacturing industries in accomplishing sustainable development. however, enterprises need to work more actively on improving less significant issues of TP. Research limitations/implications In the present investigation, contributions made by TP practices have been evaluated to accomplish sustainable development in Indian manufacturing industries. Hence, the results obtained may need some modifications before applying to other countries. Moreover, issue−wise independent modeling can also be performed to assess the importance of TP strategies under specific orientations. Practical implications The research gives priority to enhancement in the planning among various TP practices and sustainable development indicators in the industries to impart TP as an important practice to meet various challenges of competent markets worldwide. Social implications It has been exhibited from the observations that adequate TP strategies can efficiently contribute toward recognition of sustainable development to compete in the highly progressive global market. The results of various inter−relationships among TP practices and sustainable development indicators represent the effectiveness of TP practices for accomplishment of social and organizational objectives. Originality/value It has been investigated in the present study that TP practices are significant initiatives taken by the manufacturing industries for performance improvement and sustainable development. The paper elaborates the study to find out TP issues that need to be assessed significantly to avail the advantages of sustainable development and to meet the challenges posed by global market. The inter−relationships among TP strategies and sustainable development indicators have been analyzed using various statistical tools and techniques, such as inter−item covariance test; Pearson’s correlation analysis; multiple regression analysis; analytic hierarchy process and canonical correlation analysis.

Evaluating Testing, Profile Likelihood Confidence Interval Estimation, and Model Comparisons for Item Covariate Effects in Linear Logistic Test Models.

The linear logistic test model (LLTM) has been widely applied to investigate the effects of item covariates on item difficulty. The LLTM was extended with random item residuals to account for item differences not explained by the item covariates. This extended LLTM is called the LLTM-R. In this article, statistical inference methods are investigated for these two models. Type I error rates and power are compared via Monte Carlo studies. Based on the simulation results, the use of the likelihood ratio test (LRT) is recommended over the paired-sample t test based on sum scores, the Wald z test, and information criteria, and the LRT is recommended over the profile likelihood confidence interval because of the simplicity of the LRT. In addition, it is concluded that the LLTM-R is the better general model approach. Inferences based on the LLTM while the LLTM-R is the true model appear to be largely biased in the liberal way, while inferences based on the LLTM-R while the LLTM is the true model are only biased in a very minor and conservative way. Furthermore, in the absence of residual variance, Type I error rate and power were acceptable except for power when the number of items is small (10 items) and also the number of persons is small (200 persons). In the presence of residual variance, however, the number of items needs to be large (80 items) to avoid an inflated Type I error and to reach a power level of .90 for a moderate effect.

Antipsychotic Medication Adherence Scale (AMAS): Development and preliminary psychometric properties

IntroductionAlthough being highly consensual that antipsychotic adherence is an important outcome predictor in psychosis, existing reviews have found mean rates of adherence around 40–60%. Several aspects, such as patient-related, medication-related, environmental-related variables have been described as important predictors.AimsThis study aim is to develop, administer and present preliminary psychometric properties of a new scale for antipsychotic medication adherence that includes different types of predictors (clinical, psychosocial, and practical among others).MethodsThe “AMAS” was developed by a multidisciplinary team and was based on recent research on factors influencing antipsychotic adherence. The scale evolved from multiple drafts and experts were contacted in order to improve the final version. Over 50 patients with a diagnosis of a psychotic-spectrum disorder taking antipsychotic medication will be assessed with the “AMAS” and the Medication Adherence Rating Scale. Additionally, each patient's psychiatrist will fill in a form with demographic and clinical variables (such as type of symptoms, previous adherence problems, current adherence, insight and other relevant variables).ResultsThis is an ongoing study and the sample is still being collected (scheduled finish date: February/2016). Our statistical analysis’ plan includes: reliability analysis (Chronbach's alpha, alpha if item deleted, inter item correlations and covariances and item-total correlations); validity (convergent validity); factorial analysis.ConclusionsIt is hypothesized that the “AMAS” will be a practical, reliable and valid unidimentional instrument with clinical utility assessing adherence to antipsychotics. The “AMAS” can be also useful in assessing intervention targets (e.g. psychoterapeutical, psychoeducational) to enhance adherence.Disclosure of interestThe authors have not supplied their declaration of competing interest.

Development of the Work Intention Inventory Short–Form

The Work Intention Inventory (WII: Zigarmi, Nimon, Houson, Witt, &amp; Diehl, 2012) was designed to assess five measures of work intention. Measuring employee intentions is important to consider when evaluating outcomes associated with employee engagement or work passion as research indicates intentions are strong predictors of behavior. Following scale reduction procedures developed by Stanton, Sinar, Balzer, and Smith (2002), we used inter–item covariance matrices from Zigarmi et al. (2012) and data resulting from the field test of the WII–Short Form (WII–SF) in a manufacturing company to develop a short form of the WII and provide initial evidence of construct validity. There is preliminary evidence to indicate that the WII–SF may offer practitioners and researchers an efficient way to reliably and validly assess employee work intentions

The Balance-Scale Task Revisited: A Comparison of Statistical Models for Rule-Based and Information-Integration Theories of Proportional Reasoning.

We propose and test three statistical models for the analysis of children’s responses to the balance scale task, a seminal task to study proportional reasoning. We use a latent class modelling approach to formulate a rule-based latent class model (RB LCM) following from a rule-based perspective on proportional reasoning and a new statistical model, the Weighted Sum Model, following from an information-integration approach. Moreover, a hybrid LCM using item covariates is proposed, combining aspects of both a rule-based and information-integration perspective. These models are applied to two different datasets, a standard paper-and-pencil test dataset (N = 779), and a dataset collected within an online learning environment that included direct feedback, time-pressure, and a reward system (N = 808). For the paper-and-pencil dataset the RB LCM resulted in the best fit, whereas for the online dataset the hybrid LCM provided the best fit. The standard paper-and-pencil dataset yielded more evidence for distinct solution rules than the online data set in which quantitative item characteristics are more prominent in determining responses. These results shed new light on the discussion on sequential rule-based and information-integration perspectives of cognitive development.

Validity and Reliability Assessment Tool of Nursing Students Professional Behavior

Introduction: Shieffield Peer Review Assessment (SPRAT) is an instrument to assess medical student’s performance using Multi Source Feedback (MSF) method. The previous study stated that MSF with SPRAT is an effective tool assessing professional behaviour (PB) of nursing students both in clinical setting and community setting. However it needs more items to be added. Based on that explanation, it needs conducting validity and reliability test to make sure that the tool is valid and reliable.Method: There were two types of validity test used, content validity test and construct validity test as well as reliability test, namely inter-rater reliability test and item covariance test. Participants were four clinical instructors and 116 nursing students. Result: Content validity test showed that two items must be added as part of assessment item, namely diciplines and faithness. Furthermore construct validity test showed that five items were not valid since they had pearson correlation score &lt;0.3. However the items were included as consideration of nursing students’s PB. Inter-rater reliability test and item covariance reliability test showed that the tool was reliable with score 0.460 and 0.912 respectively.Discussion: The assessment tool can be applied to assess PB of nursing students since it valid and reliable. It needs to investigate the effectiveness of the tool in difference of PB of nursing students.

Validity and Reliability Assessment Tool of Nursing Students Professional Behavior

Introduction: Shieffield Peer Review Assessment (SPRAT) is an instrument to assess medical student’s performance using Multi Source Feedback (MSF) method. The previous study stated that MSF with SPRAT is an effective tool assessing professional behaviour (PB) of nursing students both in clinical setting and community setting. However it needs more items to be added. Based on that explanation, it needs conducting validity and reliability test to make sure that the tool is valid and reliable. Method: There were two types of validity test used, content validity test and construct validity test as well as reliability test, namely inter-rater reliability test and item covariance test. Participants were four clinical instructors and 116 nursing students. Result: Content validity test showed that two items must be added as part of assessment item, namely diciplines and faithness. Furthermore construct validity test showed that five items were not valid since they had pearson correlation score &lt;0.3. However the items were included as consideration of nursing students’s PB. Inter-rater reliability test and item covariance reliability test showed that the tool was reliable with score 0.460 and 0.912 respectively. Discussion: The assessment tool can be applied to assess PB of nursing students since it valid and reliable. It needs to investigate the effectiveness of the tool in difference of PB of nursing students.Keywords: validity, reliability, assessment tool of PB (professional behaviour)

A Canadian Investigation of the Psychometric Properties of the Student Motivation and Learning Strategies Inventory

The psychometric properties of the Student Motivation and Learning Strategies Inventory (SMALSI) were examined using a sample of 404 Grade 6 students from an urban Canadian school system. Students completed the SMALSI and school factors included final school grades, attendance records, and language arts, mathematics, science, and social studies results from Provincial Achievement Tests (PATs). Confirmatory factor analysis of SMALSI demonstrated less than adequate fit for each individual SMALSI factor though with some covariance of similar items, the model fit approached acceptable limits for most factors. Results generally confirmed that the SMALSI subscales were significantly related to all of the achievement variables including PAT results and final school grades. Structural equation modeling demonstrated that writing and research skills, test-taking skills, low motivation, and test anxiety all contributed to the prediction of PAT results. Test anxiety was a significant predictor of achievement across all subject areas. Canadian Grade 6 students demonstrated lower motivation, less test anxiety, and fewer attention problems but were otherwise comparable with the U.S. sample. Results provide convergent evidence supporting the psychometric properties of the SMALSI with a Canadian sample; however, there is some room to improve the overall model fit in subsequent revisions of this measure.

Psychometric Evaluation of the Thought–Action Fusion Scale in a Large Clinical Sample

This study examined the psychometric properties of the 19-item Thought-Action Fusion (TAF) Scale, a measure of maladaptive cognitive intrusions, in a large clinical sample (N = 700). An exploratory factor analysis (n = 300) yielded two interpretable factors: TAF Moral (TAF-M) and TAF Likelihood (TAF-L). A confirmatory bifactor analysis was conducted on the second portion of the sample (n = 400) to account for possible sources of item covariance using a general TAF factor (subsuming TAF-M) alongside the TAF-L domain-specific factor. The bifactor model provided an acceptable fit to the sample data. Results indicated that global TAF was more strongly associated with a measure of obsessive-compulsiveness than measures of general worry and depression, and the TAF-L dimension was more strongly related to obsessive-compulsiveness than depression. Overall, results support the bifactor structure of the TAF in a clinical sample and its close relationship to its neighboring obsessive-compulsiveness construct.

Abstract A22: The Kin KeeperSM Intervention: Women move beyond psychological barriers to Pap screening

Abstract Cancer health disparities are underlined by structural and conceptual barriers, such as: Adequate cancer awareness and education, functional cancer literacy, appropriate and timely access to cancer screening and follow-up care, and psychological aspects of the decision to undergo cancer screening. Cervical cancer health disparities can be impacted by early detection and screening with the Papanicolaou (Pap) test. The Kin KeeperSM Cancer Prevention Intervention is a culturally and linguistically tailored breast and cervical cancer educational intervention designed to improve functional cancer literacy. The Health Belief Model (HBM) was used as a framework to explore potential associations between responses to a cervical Cancer Literacy Assessment Tool (C-CLAT) item assessing a psychological barrier to Pap screening and a woman's screening accomplishments. Methods: The Kin KeeperSM model has three levels of participants: community health worker (CHW), CHW's female clients (“kin keepers”), and female family members of female clients. Trained CHWs recruited 543 Black, Latina, and Arab women from Detroit and Dearborn, MI to participate in the two-year study. Analysis included only women with two years of data, thus the final number of participants was 446 (117 Black, 157 Latina, 172 Arab). Kin keepers recruited female family members in year one and delivered the cervical cancer educational intervention in year two. After recruitment, CHWs from three local agencies administered the C-CLAT to all participants in English, Spanish, or Arabic before administering an educational intervention (pre-C-CLAT) and after the educational intervention (post-C-CLAT 1); and provided women with Personal Action Plans (PAPs) to identify screening goals based on three statements: Find a health care provider to do first-ever Pap; schedule first-ever Pap; and continue getting yearly Pap. The outcome of interest was indication of these goals as accomplishments in year two. After kin keepers delivered the educational intervention in year two, CHWs administered a post-C-CLAT 2 and an accomplishment-oriented PAP to all participants. Using multivariable logistic regression, we observed the potential effect of responses to a C-CLAT item and sociodemographic covariates on PAP accomplishments. The C-CLAT item “Getting a Pap test is very painful,” suggests a psychological barrier to screening, thus it is relevant to a classic HBM construct, perceived barriers. Post-C-CLAT 1 responses to this item were scored with an answer key and SPSS (PASW Statistics 18) was used for statistical analyses. Results: In year one, the most significant covariates affecting the goals women selected were race, relationship to the kin keeper, and health insurance status. Response to the C-CLAT item “Getting a Pap test is very painful” was not significant to the goal to continue annual Pap tests, yet race and possibly relationship to the kin keeper were significant (with an alpha of .105, p-values were .038 and .104, respectively). Analysis of women's PAP accomplishments 12 months later indicates the majority of women found a health care provider for a first-ever Pap test, scheduled a Pap in the past 12 months, and had a Pap in the past 12 months. Relationship to the kin keeper was the only statistically significant covariate (p = .035) in analysis of having had a Pap test in the last 12 months. Conclusions: Future interventions designed to impact cervical cancer health disparities should support women's intentions to pursue screening despite potential psychological barriers. Such studies should explore dynamics between female family members and how these relationships might modify screening decisions and accomplishments. This research was funded by National Institutes of Health (NIH), National Institute for Nursing Research (NINR), 1R01NR011323. Citation Information: Cancer Epidemiol Biomarkers Prev 2011;20(10 Suppl):A22.

Latent Class Detection and Class Assignment: A Comparison of the MAXEIG Taxometric Procedure and Factor Mixture Modeling Approaches

Taxometric procedures such as MAXEIG and factor mixture modeling (FMM) are used in latent class clustering, but they have very different sets of strengths and weaknesses. Taxometric procedures, popular in psychiatric and psychopathology applications, do not rely on distributional assumptions. Their sole purpose is to detect the presence of latent classes. The procedures capitalize on the assumption that, due to mean differences between two classes, item covariances within class are smaller than item covariances between the classes. FMM goes beyond class detection and permits the specification of hypothesis-based within-class covariance structures ranging from local independence to multidimensional within-class factor models. In principle, FMM permits the comparison of alternative models using likelihood-based indexes. These advantages come at the price of distributional assumptions. In addition, models are often highly parameterized and susceptible to misspecifications of the within-class covariance structure. Following an illustration with an empirical data set of binary depression items, the MAXEIG procedure and FMM are compared in a simulation study focusing on class detection and the assignment of subjects to the latent classes. FMM generally outperformed MAXEIG in terms of class detection and class assignment. Substantially different class sizes negatively impacted the performance of both approaches, whereas low class separation was much more problematic for MAXEIG than for the FMM.