Investigating the performance of level-specific fit indices in multilevel confirmatory factor analysis with dichotomous indicators: A Monte Carlo study.

We conducted a Monte Carlo study to examine the performance of level-specific χ2 test statistics and fit regarding their capacity to determine model fit at specific levels in multilevel confirmatory factor analysis with dichotomous indicators. Five design factors-numbers of groups (NG), group size (GS), intra-class correlation (ICC), thresholds of dichotomous indicators (THR), and factor loadings (FL)-were considered in this study. According to our simulation results, we recommend that practitioners should be aware that the performance of between-level-specific (b-l-s) χ2 and fit indices was mainly influenced by ICC and FL, followed by NG. At the same time, THR could slightly weigh in the performance of b-l-s fit indices in some conditions. Both b-l-s χ2 and fit indices were more promising indicators to correctly indicate model fit when ICC or FL increased. A small to medium NG (50-100) might be sufficient for b-l-s χ2 and fit indices only if both ICC and factor loadings were high, while in remaining conditions, an NG of 200 was needed. Moreover, practitioners could use within-level-specific (w-l-s) χ2 and fit indices (except for RMSEAW) along with traditional cut-off values to evaluate within-level models comprising dichotomous indicators. W-l-s χ2 and fit indices were more promising to determine model fit when FL increased. THR had a slight impact and could weigh in the performance of [Formula: see text], RMSEAW, CFIW, and TLIW. Unfortunately, RMSEAW was heavily affected by FL and THR and could determine model fit only when FL was high and THR was symmetric.

Oral presentation assessment and image reading behaviour on brain computed tomography reading in novice clinical learners: an eye-tracking study.

BACKGROUND: To study whether oral presentation (OP) assessment could reflect the novice learners' interpretation skills and reading behaviour on brain computed tomography (CT) reading. METHODS: Eighty fifth-year medical students were recruited, received a 2-hour interactive workshop on how to read brain CT, and were assigned to read two brain CT images before and after instruction. We evaluated their image reading behaviour in terms of overall OP post-test rating, the lesion identification, and competency in systematic image reading after instruction. Students' reading behaviour in searching for the target lesions were recorded by the eye-tracking technique and were used to validate the accuracy of lesion reports. Statistical analyses, including lag sequential analysis (LSA), linear mixed models, and transition entropy (TE) were conducted to reveal temporal relations and spatial complexity of systematic image reading from the eye movement perspective. RESULTS: The overall OP ratings [pre-test vs. post-test: 0 vs. 1 in case 1, 0 vs. 1 in case 2, p < 0.001] improved after instruction. Both the scores of systematic OP ratings [0 vs.1 in both cases, p < 0.001] and eye-tracking studies (Case 1: 3.42 ± 0.62 and 3.67 ± 0.37 in TE, p = 0.001; Case 2: 3.42 ± 0.76 and 3.75 ± 0.37 in TE, p = 0.002) showed that the image reading behaviour changed before and after instruction. The results of linear mixed models suggested a significant interaction between instruction and area of interests for case 1 (p < 0.001) and case 2 (p = 0.004). Visual attention to the target lesions in the case 1 assessed by dwell time were 506.50 ± 509.06 and 374.38 ± 464.68 milliseconds before and after instruction (p = 0.02). However, the dwell times in the case 2, the fixation counts and the frequencies of accurate lesion diagnoses in both cases did not change after instruction. CONCLUSION: Our results showed OP performance may change concurrently with the medical students' reading behaviour on brain CT after a structured instruction.

Evaluating fit indices in a multilevel latent growth curve model: A Monte Carlo study.

The multilevel latent growth curve model (MLGCM), which is subsumed by the multilevel structural equation modeling framework, has been advocated as a means of investigating individual and cluster trajectories. Still, how to evaluate the goodness of fit of MLGCMs has not been well addressed. The purpose of this study was to conduct a systematic Monte Carlo simulation to carefully investigate the effectiveness of (a) level-specific fit indices and (b) target-specific fit indices in an MLGCM, in terms of their independence from the sample size's influence and their sensitivity to misspecification in the MLGCM that occurs in either the between-covariance, between-mean, or within-covariance structure. The design factors included the number of clusters, the cluster size, and the model specification. We used Mplus 7.4 to generate simulated replications and estimate each of the models. We appropriately controlled the severity of misspecification when we generated the simulated replications. The simulation results suggested that applying RMSEAT_S_COV, TLIT _ S _ COV, and SRMRB maximizes the capacity to detect misspecifications in the between-covariance structure. Moreover, the use of RMSEAPS _ B, CFIPS _ B, and TLIPS _ B is recommended for evaluating the fit of the between-mean structure. Finally, we found that evaluation of the within-covariance structure turned out to be unexpectedly challenging, because none of the within-level-specific fit indices (RMSEAPS _ W, CFIPS _ W, TLIPS _ W, and SRMRW) had a practically significant sensitivity.

Analyzing individual growth with clustered longitudinal data: A comparison between model-based and design-based multilevel approaches.

To prevent biased estimates of intraindividual growth and interindividual variability when working with clustered longitudinal data (e.g., repeated measures nested within students; students nested within schools), individual dependency should be considered. A Monte Carlo study was conducted to examine to what extent two model-based approaches (multilevel latent growth curve model - MLGCM, and maximum model - MM) and one design-based approach (design-based latent growth curve model - D-LGCM) could produce unbiased and efficient parameter estimates of intraindividual growth and interindividual variability given clustered longitudinal data. The solutions of a single-level latent growth curve model (SLGCM) were also provided to demonstrate the consequences of ignoring individual dependency. Design factors considered in the present simulation study were as follows: number of clusters (NC = 10, 30, 50, 100, 150, 200, and 500) and cluster size (CS = 5, 10, and 20). According to our results, when intraindividual growth is of interest, researchers are free to implement MLGCM, MM, or D-LGCM. With regard to interindividual variability, MLGCM and MM were capable of producing accurate parameter estimates and SEs. However, when D-LGCM and SLGCM were applied, parameter estimates of interindividual variability were not comprised exclusively of the variability in individual (e.g., students) growth but instead were the combined variability of individual and cluster (e.g., school) growth, which cannot be interpreted. The take-home message is that D-LGCM does not qualify as an alternative approach to analyzing clustered longitudinal data if interindividual variability is of interest.

Brain computed tomography reading of stroke patients by resident doctors from different medical specialities: An eye-tracking study.

BACKGROUND: Using the eye-tracking technique, our work aimed to examine whether difference in clinical background may affect the training outcome of resident doctors' interpretation skills and reading behaviour related to brain computed tomography (CT). METHODS: Twelve resident doctors in the neurology, radiology, and emergency departments were recruited. Each participant had to read CT images of the brain for two cases. We evaluated each participant's accuracy of lesion identification. We also used the eye-tracking technique to assess reading behaviour. We recorded dwell times, fixation counts, run counts, and first-run dwell times of target lesions to evaluate visual attention. Transition entropy was applied to assess the temporal relations and spatial dynamics of systematic image reading. RESULTS: The eye-tracking results showed that the image reading sequence examined by transition entropy was comparable among resident doctors from different medical specialties (p = 0.82). However, the dwell time of the target lesions was shorter for the resident doctors from the neurology department (4828.63 ms, p = 0.01) than for those from the resident doctors from the radiology (6275.88 ms) and emergency (5305.00 ms) departments. The eye-tracking results in individual areas of interest only showed differences in the eye-tracking performance of the first-run dwell time (p = 0.05) in the anterior cerebral falx. DISCUSSION: Our findings demonstrate that resident doctors from different medical specialties may achieve similar imaging reading patterns for brain CT. This may mitigate queries regarding the influence of different backgrounds on training outcomes.

Comparisons of Science Motivational Beliefs of Adolescents in Taiwan, Australia, and the United States: Assessing the Measurement Invariance Across Countries and Genders.

This study utilized international, large-scale assessment data to compare science motivational beliefs of adolescents within and between countries and genders. The study focused on the beliefs about science of eighth graders, including their self-concept in science, the intrinsic value they ascribed to science, and their beliefs about the utility of the subject. The study data were derived from the Trends in International Mathematics and Science Study in 2019 (TIMSS) that was conducted in Taiwan, Australia, and the United States. To ensure the validity of mean cross-group comparisons, the measurement invariance (MI) of the constructs was first assessed. The multiple-group confirmatory factor analysis and latent factor mean comparisons were applied to the data. The results indicated that the MI of science motivational beliefs across the three countries attained only metric invariance, rendering a latent mean comparison implausible. However, the cross-gender MI within each country attained scalar invariance, supporting the comparison of means across genders. The science motivational beliefs of females were significantly lower than those of males, with the exception of beliefs of US students about their utility value. The findings of this study raise concerns about the validity of current international comparisons of science motivational beliefs of the students while supporting the use of TIMSS data to identify gender differences in science motivation within each country. The implications of MI across countries and genders are discussed, and the importance of establishing MI is highlighted. The findings affirm that gender disparities in science motivational beliefs can be compared using constructs with sound psychometric properties.

Using iMCFA to Perform the CFA, Multilevel CFA, and Maximum Model for Analyzing Complex Survey Data.

To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to investigate potential multilevel structure of survey data. Using iMCFA, researchers can visually set the between- and within-level factorial structure to fit MCFA, CFA and/or MAX MCFA models for complex survey data. iMCFA can then yield between- and within-level variance-covariance matrices, calculate intraclass correlations, perform the analyses and generate the outputs for respective models. The summary of the analytical outputs from LISREL is gathered and tabulated for further model comparison and interpretation. iMCFA also provides LISREL syntax of different models for researchers' future use. An empirical and a simulated multilevel dataset with complex and simple structures in the within or between level was used to illustrate the usability and the effectiveness of the iMCFA procedure on analyzing complex survey data. The analytic results of iMCFA using Muthen's limited information estimator were compared with those of Mplus using Full Information Maximum Likelihood regarding the effectiveness of different estimation methods.

A Solution to Modeling Multilevel Confirmatory Factor Analysis with Data Obtained from Complex Survey Sampling to Avoid Conflated Parameter Estimates.

The issue of equality in the between-and within-level structures in Multilevel Confirmatory Factor Analysis (MCFA) models has been influential for obtaining unbiased parameter estimates and statistical inferences. A commonly seen condition is the inequality of factor loadings under equal level-varying structures. With mathematical investigation and Monte Carlo simulation, this study compared the robustness of five statistical models including two model-based (a true and a mis-specified models), one design-based, and two maximum models (two models where the full rank of variance-covariance matrix is estimated in between level and within level, respectively) in analyzing complex survey measurement data with level-varying factor loadings. The empirical data of 120 3rd graders' (from 40 classrooms) perceived Harter competence scale were modeled using MCFA and the parameter estimates were used as true parameters to perform the Monte Carlo simulation study. Results showed maximum models was robust to unequal factor loadings while the design-based and the miss-specified model-based approaches produced conflated results and spurious statistical inferences. We recommend the use of maximum models if researchers have limited information about the pattern of factor loadings and measurement structures. Measurement models are key components of Structural Equation Modeling (SEM); therefore, the findings can be generalized to multilevel SEM and CFA models. Mplus codes are provided for maximum models and other analytical models.

Quantitative membrane loading of polymer vesicles.

We utilize a series of structurally homologous, multi-porphyrin-based, fluorophores (PBFs) in order to explore the capacity of polymer vesicles (polymersomes) to stably incorporate large hydrophobic molecules, non-covalently within their thick lamellar membranes. Through aqueous hydration of dry, uniform thin-films of amphiphilic polymer and PBF species deposited on Teflon, self-assembled polymersomes are readily generated incorporating the hydrophobic fluorophores in prescribed molar ratios within their membranes. The size-dependent spectral properties of the PBFs allow for ready optical verification ( steady-state absorption and emission spectroscopy) of the extent of vesicle membrane loading and enable delineation of intermembranous molecular interactions. The resultant effects of PBF membrane-loading on polymersome thermodynamic and mechanical stability are further assessed by cryogenic transmission electron microscopy (cryo-TEM) and micropipet aspiration, respectively. We demonstrate that polymersomes can be loaded at up to 10 mol/wt% concentrations, with hydrophobic molecules that possess sizes comparable to those of large pharmaceutical conjugates ( ranging 1.4-5.4 nm in length and = 0.7-5.4 kg mol), without significantly compromising the robust thermodynamic and mechanical stabilities of these synthetic vesicle assemblies. Due to membrane incorporation, hydrophobic encapsulants are effectively prevented from self-aggregation, able to be highly concentrated in aqueous solution, and successfully shielded from deleterious environmental interactions. Together, these studies present a generalized paradigm for the generation of complex multi-functional materials that combine both hydrophilic and hydrophobic agents, in mesoscopic dimensions, through cooperative self-assembly.

Graduates' perceptions of their clinical competencies in allergy and immunology: results of a survey.

PURPOSE: The Accreditation Council for Graduate Medical Education (ACGME) and the American Board of Medical Specialties (ABMS) have identified six areas of general competency. This study surveyed graduates of allergy and immunology training programs about their perceived clinical competency and the adequacy of their subspecialty training. METHOD: In August 2000 and May 2001, a questionnaire was mailed to 373 physicians who had completed a fellowship in allergy and immunology in the United States between 1995 and 2001. Physicians were asked to rate the perceived importance and adequacy of their training in, and their level of competency for, 57 general competencies and subspecialty-specific competencies and procedures. RESULTS: A total of 253 physicians responded (68%). All items in the six ACGME/ABMS general competencies had high ratings (>/= 90%) for perceived importance. One item in the practice-based learning area had low ratings for adequacy of training (57%) and intermediate for competency (75%). Two items in the system-based practice area had low ratings for training (65% and 67%) and intermediate for competency (86% and 88%). Generally, core specialty-specific items (allergic rhinitis, asthma, and urticaria) had high ratings (>/= 90%) for importance, training, and competency. Without exception, items with ratings of less than 70% for adequacy of training also had ratings of less than 90% for competency. CONCLUSION: The general competencies were considered important, but training in system-based practice and practice-based learning may be deficient. Although self-perceived competency in core areas of allergy and immunology was high, weaknesses in training and self-perceived competency in selected areas were identified.

Family practice graduate preparedness in the six ACGME competency areas: prequel.

BACKGROUND AND OBJECTIVES: Since July 2002, family practice residency program accreditation requires evidence of teaching and assessing residents in six competency areas. This study was conducted to obtain baseline information about family practice graduates' perceptions of the importance of specific competencies and the extent to which residency training prepared them to perform skills representative of the six competency areas. METHODS: A national, cross-sectional survey was conducted of family physicians who had graduated from residency programs from 1998 to 2000. RESULTS: The response rate was 54% (n=1,228). Graduates reported the most preparation in patient care skills, followed by interpersonal and communication skills and then professionalism. The least preparation was reported for skills pertinent to practice-based learning and improvement, systems-based practice, and some areas of professionalism. CONCLUSIONS: Areas of residency education that appear to warrant improvement include education about system aspects of care, practice-based learning and improvement, and selected professionalism issues.

Leuko-polymersomes.

Polymersomes are vesicles whose membranes are comprised of self-assembled amphiphilic block co-polymers. Synthetic control of block co-polymer chemistry provides an advantageous diversity of polymersome functions, ranging from tunable materials strength, superior encaspulation of hydrophobic and hydrophilic drugs and optical dyes, and facile functionalization. We have exploited polymersome tunability to make leuko-polymersomes: polymersomes with the adhesive properties of leukocytes. By functionalizing the terminal groups on the outer shell of the vesicle with biotin, we have used modular avidin-biotin chemistry to attach adhesion ligands that mimic the two critical adhesion pathways that leukocytes utilize to achieve adhesion in the fast fluid flow of blood vessels--selectins and integrins. We demonstrate that adhesion is specific and is supported at hydrodynamic flow rates at which leukocytes adhere. We envision the use of such particles for monitoring or treating inflammation, cancer and cardiovascular disease.

Adhesion of antibody-functionalized polymersomes.

Polymersomes are vesicles made from synthetic block copolymers. The adhesiveness of micron-sized polymersomes, functionalized with antibodies that bind to vascular cell adhesion molecules, which could be useful for vascular targeting, was measured. Intercellular adhesion molecule-1 (ICAM-1) is an endothelial cell adhesion molecule whose expression increases during inflammatory disease, and is therefore a natural target for vascular delivery. We functionalized polymersomes with an anti-ICAM-1 antibody, using modular biotin-avidin chemistry. Micropipet aspiration was used to confirm specific adhesion and measure the adhesion strength between an anti-ICAM-1-coated polymersome and an ICAM-1-coated polystyrene microsphere at various surface densities of adhesion molecules. The adhesion is kinetically trapped, and adhesion strength is quantified by the critical tension for detachment. The adhesion strength increases in proportion to the surface density of anti-ICAM-1 molecules, in contrast to results seen previously when measuring adhesion between biotinylated vesicles and avidin-coated beads (Lin et al. Langmuir 2004, 20, 5493). The difference in dependence on the density of functional groups is likely due to the molecular presentation at the vesicle surface; in the current study, the presentation of biotinylated anti-ICAM-1 on a layer of avidin leads to the effective presentation of the anti-ICAM-1 and, thus, a monotonic increase in adhesiveness with antibody density.

Adhesion of polymer vesicles.

The adhesion and bending modulus of polybutadiene-poly(ethylene oxide) block copolymer vesicles made from a bidisperse mixture of polymers is measured using micropipette aspiration. The adhesion energy between biotinylated vesicles and avidin beads is modeled by incorporating the extension of the adhesive ligands above the surface brush of the vesicle according to the blob model of bidisperse polymer mixtures of Komura and Safran assuming the polymer brush at the surface of the vesicle is compact. The same model accurately reproduces the scaling of the bending modulus with polymer composition.

The effect of polymer chain length and surface density on the adhesiveness of functionalized polymersomes.

Giant cell-like polymer vesicles, polymersomes, made from the diblock copolymer poly(ethylene oxide)-polybutadiene (PEO-PBD), have bilayer structures similar to the cell membrane but have superior and tunable properties for storage and stability. We have modified the terminal hydroxyl of the hydrophilic block with biotin-lysine (biocytin), a biologically derived group that imparts specific adhesiveness to a polymer colloid coated with avidin. The functionalized polymer will form vesicles, either on its own or when mixed with unmodified block copolymers that also form vesicles. The incorporation and mixing of the functionalized polymer into vesicle bilayers is measured using a fluorescent version ofbiocytin with confocal microscopy. The fluorescence signal associated with the vesicle is in proportion with the concentration of functional polymer added during vesicle construction. The adhesiveness of polymer vesicles containing functionalized biotinylated polymer to avidin coated microspheres is measured with micropipet aspiration. Two types of polymer vesicles were constructed: one where the functionalized polymer (molecular weight (MW), 10400 Da) was longer than the surrounding unfunctionalized polymer (MW, 3600 Da) and one where the functionalized polymer (MW, 10400 Da) was the same length as the unfunctionalized polymer. In all cases, the avidin-biotin bonds form kinetically trapped crossbridges that impart little tension as they form but require significantly more tension to break. The relative length of the functionalized polymer on the surface of the vesicle is an important determinant for the adhesion of a polymer vesicle but not for the adsorption of soluble avidin. Greater adhesion strengths are seen where the functionalized polymer is longer than the surrounding polymer. The concentration of functionalized polymer at which adhesion is maximal depends on the relative lengths of the polymers. When the functionalized polymer is the same length as the surface brush of the polymersome membrane, the critical tension is maximal at 10 mol % functionalized polymer concentration. However, when the biocytin groups are attached to a polymer which is larger than the surface brush, the critical tension is maximal at 55 mol % functionalized polymer. These results indicate that polymer mixing and length can control the interfacial adhesion of polymer brushes and must be understood to tune polymersome adhesiveness.