Fractional Anisotropy in Selected, Motor-Related White Matter Tracts and Its Cross-Sectional and Longitudinal Associations With Motor Function in Healthy Older Adults

Background

While it is well-known that deficits in motor performance and brain structural connectivity occur in the course of healthy aging, it is still unclear if and how these changes are related to each other. While some cross-sectional studies suggest that white matter (WM) microstructure is positively associated with motor function in healthy older adults, more evidence is needed. Moreover, longitudinal data is required to estimate whether similar associations can be found between trajectories of change in WM microstructure and motor function. The current study addresses this gap by investigating age-associations and longitudinal changes in WM microstructure and motor function, and the cross-sectional (level-level) and longitudinal (level-change, change-change) association between these two domains.

Method

We used multiple-occasion data (covering 4 years) from a large sample (N = 231) of healthy older adults from the Longitudinal Healthy Aging Brain (LHAB) database. To measure WM microstructure, we used diffusion-weighted imaging data to compute mean FA in three selected WM tracts [forceps minor (FMIN); superior longitudinal fasciculus (SLF); corticospinal tract (CST)]. Motor function was measured via two motor speed tests (grooved pegboard, finger tapping) and one motor strength test (grip force test), separately for the left and the right hand. The statistical analysis was conducted with longitudinal growth curve models in the structural equation modeling framework.

Results

The results revealed longitudinal decline and negative cross-sectional age-associations for mean WM FA in the FMIN and SLF, and for motor function in all tests, with a higher vulnerability for left than right hand motor performance. Regarding cross-domain associations, we found a significant positive level-level correlation among mean WM FA in the FMIN with motor speed. Mean FA in SLF and CST was not correlated with motor performance measures, and none of the level-change or change-change associations were significant. Overall, our results (a) provide important insights into aging-related changes of fine motor abilities and FA in selected white matter tracts associated with motor control, (b) support previous cross-sectional work showing that neural control of movement in older adults also involves brain structures outside the core motor system and (c) align with the idea that, in healthy aging, compensatory mechanisms may be in place and longer time delays may be needed to reveal level-change or change-change associations.

The Impact of Adolescent Internet Addiction on Sexual Online Victimization: The Mediating Effects of Sexting and Body Self-Esteem

Adolescents’ problematic use of the internet and the risk of sexual online victimization are an increasing concern among families, researchers, professionals and society. This study aimed to analyze the interplay between adolescents’ addiction to social networks and internet, body self-esteem and sexual–erotic risk behavior online: sexting, sextortion and grooming. While sexting refers to the voluntary engagement in texting sexual–erotic messages, sextortion and grooming are means of sexual–erotic victimization through the use of the internet. Participants were 1763 adolescents (51% girls), aged 12 to 16 years (M = 14.56; SD = 1.16), from public (n = 1068; 60.60%) and private (n = 695; 39.40%) high schools in the Basque Country (Spain). We carried out structural equation modeling (SEM) using Mplus to assess the mediating effects of body self-esteem in the relationship between addiction to social media and internet and sexual–erotic risk behavior. The results showed that internet addiction predicts online sexual victimization; specifically, the best predictors of sexting, sextortion and grooming victimization were symptoms of internet addiction and geek behavior. Body self-esteem and sexting mediated the relationship between internet addiction and sexual online victimization in adolescents. These results highlight the importance of attending to adolescents’ mental health regarding their online behavior, considering the risk and protective factors involved, due to its close association with online sexual victimization.

School Violence and Teacher Professional Engagement: A Cross-National Study

School violence research has mainly focused on the impact on students. Very few studies, even fewer from a cross-cultural perspective, have examined the relationships between school violence and teacher professional engagement, and the role played by teacher self-efficacy and school climate related factors. The present study utilizes a SEM research methodology to analyze the 2013 TALIS data. The purpose is to understand and compare the relationships in four different cultural contexts; the U.S., England, South Korea, and Mexico. Results indicate, on average, that the significant and negative impacts of school violence on teacher professional engagement are partly mediated by teacher self-efficacy. The negativity of school violence is significantly alleviated by enhancing participation among school stakeholders and improving teacher–student relationships. The relationships among the factors apply across all four cultural systems, though, the effects of factors and variables vary to a degree. The paper also discusses other relevant issues and differences as well as their implications.

Investigating into the critical factors supporting healthy independent longevity: A proposition of a conceptual model with measurements during and beyond COVID-19 pandemic

This study investigated the factors that support the elderly citizens' perceived healthy independent longevity during and beyond the COVID-19 pandemic. The Structural Equation Modeling was conducted with the 1607 dataset collected from Japan to validate a proposed model with six antecedent factors. It has been found that "Town vibrancy" and "Mobility and transportations" have the most significant impact, whereas "Health and welfare policies" and "Community bonding" have a relatively lower impact on their perceived healthy longevity. The study has provided a conceptual model with measurements for further discussions in the field of study.

Predicting mask-wearing behavior intention among international students during COVID-19 based on the theory of planned behavior

BACKGROUND

The global outbreak of the coronavirus disease 2019 (COVID-19) has emerged as a major public health threat. This study aimed to analyze the influencing factors of international students' intention to wear a mask based on the theory of planned behavior (TPB). The findings are important because they provide pertinent information in designing and implementing COVID-19 prevention programs.

METHODS

Self-designed questionnaires were distributed to 477 international students. Exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) was conducted to identify and confirm the factor structure, and the structural equation model (SEM) was applied to determine the predictors of masks wearing.

RESULTS

The final structural model was well reflected by fit indices. The research model of international students' intention to wear a mask for protection against COVID-19 was acceptable. All of the hypotheses were supported. Attitude and perceived behavioral control (PBC) were positively related to behavior intention (BI), respectively. Subjective norm (SN) also had a direct effect on attitude, PBC, and BI.

CONCLUSIONS

Referring to TPB was useful in identifying determinants of mask-wearing. The strongest predictor was SN, which indicated it was deserving of increased attention. These findings are significant to strengthen international students' awareness regarding self-protection and enhance the effectiveness of COVID-19 prevention programs.

Understanding how e-health interventions meet psychosocial needs of breast cancer patients: The pathways of influence on quality of life and cancer concerns

OBJECTIVE

This investigation explores how using different e-health interventions facilitates positive psychosocial changes and how these changes reduce cancer concerns and improve quality of life in breast cancer patients over time.

METHODS

A total of 326 breast cancer patients were randomly assigned to one of three e-health interventions: (a) Internet only, (b) the Comprehensive Health Enhancement Support System information and support services (CHESS-IS), or (c) CHESS with mentor. Proximal health outcomes such as information overload, emotional functioning, and social support were measured alongside distal outcomes like cancer concerns and quality of life. Participants completed surveys at four time points: pretest as a baseline, 6 weeks, 3 months, and 6 months.

RESULTS

Both interventions were effective in improving patient health beyond Internet only but they differed in type of change mechanism and clinical benefit. The CHESS-IS enhanced proximal outcomes at 3 months through improved information competence. The CHESS with mentor intervention reduced breast cancer concerns at 6 months, mediated mainly by emotional-social competence and emotional functioning.

CONCLUSIONS

Using e-health interventions like CHESS can help patients improve cancer information management skills and emotional functioning, contributing to better short-term health outcomes. Adding a human mentor can enhance the benefits of CHESS use, extending the experience among breast cancer patients. Theoretical, practical, and clinical implications of the study results are discussed.

The Effect of Estimation Methods on SEM Fit Indices

We examined the effect of estimation methods, maximum likelihood (ML), unweighted least squares (ULS), and diagonally weighted least squares (DWLS), on three population SEM (structural equation modeling) fit indices: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). We considered different types and levels of misspecification in factor analysis models: misspecified dimensionality, omitting cross-loadings, and ignoring residual correlations. Estimation methods had substantial impacts on the RMSEA and CFI so that different cutoff values need to be employed for different estimators. In contrast, SRMR is robust to the method used to estimate the model parameters. The same criterion can be applied at the population level when using the SRMR to evaluate model fit, regardless of the choice of estimation method.

The influence of local market and household factors on aflatoxin presence in maize and symptoms of its exposure to children in Guatemala

Recent evidence supports the hypothesis that aflatoxin exposure from maize can influence malnutrition rates among children. Therefore, in Guatemala we investigated two questions; which maize sources exposed households to higher risk of aflatoxin exposure symptoms and what the risk factors were for each maize source, pre- and post-maize harvest. Survey data and household maize samples were collected in October 2016 (pre-harvest) and February 2017 (post-harvest) in San Vicente, Guatemala. Structural equation modeling (SEM) and odds ratios were used to assess the data. The results suggested that households which purchased maize from the market had 3.64 higher odds of high levels of aflatoxin. The models identified that good market purchase habits were significant for market-based maize sources while improved post-harvest practices and improved types of maize storage were significant for subsistence-based maize sources. Cumulative results suggest multiple interventions may be effective but are dependent on time of year and source of maize.

Determinants of soil organic carbon sequestration and its contribution to ecosystem carbon sinks of planted forests

The area of forest established through afforestation/reforestation has been increasing on a global scale, which is particularly important as these planted forests attenuate climate change by sequestering carbon. However, the determinants of soil organic carbon (SOC) sequestration and their contribution to the ecosystem carbon sink of planted forests remain uncertain. By using globally distributed data extracted from 154 peer-reviewed publications and a total of 355 sampling points, we investigated above-ground biomass carbon (ABC) sequestration and SOC sequestration across three different climatic zones (tropical, warm temperate, and cold temperate) through correlation analysis, regression models, and structural equation modeling (SEM). We found that the proportion of SOC sequestration in the ecosystem C sequestration averaged 14.1% globally, being the highest (27.0%) in the warm temperate and the lowest (10.7%) in the tropical climatic zones. The proportion was mainly affected by latitude. The sink rate of ABC (R_ABC ) in tropical climates (2.48 Mg C ha^-1  year^-1 ) and the sink rate of SOC (R_SOC ) in warm temperate climates (0.96 Mg C ha^-1  year^-1 ) were higher than other climatic zones. The main determinants of R_SOC were the number of frost-free days, latitude, mean annual precipitation (MAP), and SOC density (SOCD) at the initial observation; however, these variables depended on the climatic zone. According to the SEM, frost-free period, mean annual temperature (MAT) and MAP are the dominant driving factors affecting R_SOC in Chinese plantations. MAT has a positive effect on R_SOC , and global warming may increase R_SOC of temperate plantations in China. Our findings highlight the determinants of SOC sequestration and quantitatively reveal the substantial global contribution of SOC sequestration to ecosystem carbon sink provided by planted forests. Our results help managers identify and control key factors to increase carbon sequestration in forest ecosystems.

Exploring critical factors influencing nurses' intention to use tablet PC in Patients' care using an integrated theoretical model

The use of health information technology (HIT) is expected to deliver benefits for patients, nurses, physicians, and organizations, but the benefits of HIT can only be attained if nurses accept and intend to use it as they are the leading user-group. The use of the tablet is becoming commonplace in healthcare organizations to improve patient care. The current study incorporates Technology Acceptance Model2 (TAM2) with two antecedents, facilitating condition and personal, to identify and understand the factors that influence nurses' intention to use the Tablet PC. The survey methodology was used to collect data from the nurses working in a regional healthcare center in Taiwan. The structural equation modeling (SEM) technique was employed to analyze the research framework. A total of 110 valid responses for analysis. The results suggest that the modified proposed research framework explains about 41.7% of the variance of nurses' behavioral intention. The partial least squares (PLS) regression indicated that perceived usefulness, subjective norm, and personal a positive and significant influence on nurses' intention to use the Tablet PC. But concerning the perceived ease of use, the insignificant path coefficient was reported. The finding also indicated that personal on the research model is much stronger than the subjective norm on Tablet PC performance. The proposed research framework contributes to the conclusive explanation for understanding nurses' intention to use. The current study brings perspectives from the technological and attitudinal differences that have largely been missing in the existing literature of the nurses' intention to use HIT. Thus, health care providers must take these factors into consideration as the findings of the current study advance theory and contribute to the basis for future study intended for enhancing our understanding of nurses' adoption behavior regarding HIT.

Examination of the Causality Relationship between Psychological Distress and Social Participation in Elderly People: A Pilot Study

Few studies have considered the causal relationship between psychological distress and social participation in elderly people. Here we investigated this relationship based on an initial survey and a follow-up survey. In 2016, a survey was distributed to 86 participants. A follow-up survey of 80 of those participants was performed in 2017. We adopted the following variables: psychological distress and social participation as represented by the Kessler psychological distress scale and social participation scores, respectively. By using cross-lagged and synchronous effects models, we found that the 2016 Kessler psychological distress scale had a significant influence on the 2017 social participation scores (standardization factor=-0.221, p=0.020) and the 2017 Kessler psychological distress scale significantly influenced the 2017 social participation scores (standardization factor=-0.345, p=0.039). The results suggest that psychological distress may affect social participation one year later.

The Perilous Use of Proxy Variables

It is often not stated or quantified how well measured proxy variables account for the variance in latent constructs they are intended to represent. A sensitivity analysis was run using data from the Survey of Health, Ageing and Retirement in Europe to estimate models varying in the degree to which proxy variables represent intended constructs. Results showed that parameter estimates differ substantially across different levels of variable representation. When variables are used with poor construct validity, an insufficient amount of variance is removed from the observed spurious relationship between design variable and outcome. The findings from this methodological demonstration underscore the importance of selecting proxy variables that accurately represent the underlying construct for which control is intended.

Lagged Coupled Changes Between White Matter Microstructure and Processing Speed in Healthy Aging: A Longitudinal Investigation

Age-related differences in white matter (WM) microstructure have been linked to lower performance in tasks of processing speed in healthy older individuals. However, only few studies have examined this link in a longitudinal setting. These investigations have been limited to the correlation of simultaneous changes in WM microstructure and processing speed. Still little is known about the nature of age-related changes in WM microstructure, i.e., regionally distinct vs. global changes. In the present study, we addressed these open questions by exploring whether previous changes in WM microstructure were related to subsequent changes in processing speed: (a) 1 year later; or (b) 2 years later. Furthermore, we investigated whether age-related changes in WM microstructure were regionally specific or global. We used data from four occasions (covering 4 years) of the Longitudinal Healthy Aging Brain (LHAB) database project (N = 232; age range at baseline = 64–86). As a measure of WM microstructure, we used mean fractional anisotropy (FA) in 10 major WM tracts averaged across hemispheres. Processing speed was measured with four cognitive tasks. Statistical analyses were conducted with bivariate latent change score (LCS) models. We found, for the first time, evidence for lagged couplings between preceding changes in FA and subsequent changes in processing speed 2 years, but not 1 year later in some of the WM tracts (anterior thalamic radiation, superior longitudinal fasciculus). Our results supported the notion that FA changes were different between regional WM tracts rather than globally shared, with some tracts showing mean declines in FA, and others remaining relatively stable across 4 years.

Modeling Measurement as a Sequential Process: Autoregressive Confirmatory Factor Analysis (AR-CFA)

To model data from multi-item scales, many researchers default to a confirmatory factor analysis (CFA) approach that restricts cross-loadings and residual correlations to zero. This often leads to problems of measurement-model misfit while also ignoring theoretically relevant alternatives. Existing research mostly offers solutions by relaxing assumptions about cross-loadings and allowing residual correlations. However, such approaches are critiqued as being weak on theory and/or indicative of problematic measurement scales. We offer a theoretically-grounded alternative to modeling survey data called an autoregressive confirmatory factor analysis (AR-CFA), which is motivated by recognizing that responding to survey items is a sequential process that may create temporal dependencies among scale items. We compare an AR-CFA to other common approaches using a sample of 8,569 people measured along five common personality factors, showing how the AR-CFA can improve model fit and offer evidence of increased construct validity. We then introduce methods for testing AR-CFA hypotheses, including cross-level moderation effects using latent interactions among stable factors and time-varying residuals. We recommend considering the AR-CFA as a useful complement to other existing approaches and treat AR-CFA limitations.

Comparison of Bootstrap Confidence Interval Methods for GSCA Using a Monte Carlo Simulation

Generalized structured component analysis (GSCA) is a theoretically well-founded approach to component-based structural equation modeling (SEM). This approach utilizes the bootstrap method to estimate the confidence intervals of its parameter estimates without recourse to distributional assumptions, such as multivariate normality. It currently provides the bootstrap percentile confidence intervals only. Recently, the potential usefulness of the bias-corrected and accelerated bootstrap (BCa) confidence intervals (CIs) over the percentile method has attracted attention for another component-based SEM approach—partial least squares path modeling. Thus, in this study, we implemented the BCa CI method into GSCA and conducted a rigorous simulation to evaluate the performance of three bootstrap CI methods, including percentile, BCa, and Student's t methods, in terms of coverage and balance. We found that the percentile method produced CIs closer to the desired level of coverage than the other methods, while the BCa method was less prone to imbalance than the other two methods. Study findings and implications are discussed, as well as limitations and directions for future research.

Relationship between Psychological Distress and Continuous Sedentary Behavior in Healthy Older Adults

Background: Our purpose is to clarify whether psychological distress (PD) affects the rate of continuous sedentary behavior (CSB). Materials and Methods: In this secondary analysis, a sample population of 80 healthy older adults aged 65 years or older participated in a health club of college A from 2016 to 2017. We conducted Structural Equation Modeling (SEM) using the cross-lagged and synchronous effects models. We adopted the following as proxy variables: CSB (based on the ratio of 1.5 METs sessions or more continuing for over 30 min) CSB and PD (based on the Kessler psychological distress scale: K6). Results: "2016 K6" had a significant influence on "2017 CSB" (standardization factor (β) = 0.136, p = 0.020) using the cross-lagged effects model, and "2017 K6" significantly influenced "2017 CSB" (β = 0.166, p = 0.039) using the synchronous effects model. Fit indices were Adjusted Goodness-of-Fit Index (AGFI) = 0.990, Confirmatory Fit Index (CFI) = 1.000, and Root Mean Square Error of Approximation (RMSEA) = 0.000. Conclusion: The results suggest that PD may affect the ratio of CSB one year later.

Understanding the Model Size Effect on SEM Fit Indices

This study investigated the effect the number of observed variables (p) has on three structural equation modeling indices: the comparative fit index (CFI), the Tucker-Lewis index (TLI), and the root mean square error of approximation (RMSEA). The behaviors of the population fit indices and their sample estimates were compared under various conditions created by manipulating the number of observed variables, the types of model misspecification, the sample size, and the magnitude of factor loadings. The results showed that the effect of p on the population CFI and TLI depended on the type of specification error, whereas a higher p was associated with lower values of the population RMSEA regardless of the type of model misspecification. In finite samples, all three fit indices tended to yield estimates that suggested a worse fit than their population counterparts, which was more pronounced with a smaller sample size, higher p, and lower factor loading.

Evaluating the accessibility of essential medicines in China

OBJECTIVE

To evaluate the accessibility of essential medicines in China through a new system which integrated the structure, process, and effect of the National Essential Medicine Policy (NEMP).

METHODS

A structural equation model was built to verify the reliability of the evaluation system. This study utilized the Delphi method to obtain the structure and process index data, and used the WHO/HAI standard method for the effect index data to evaluate the NEMP. Six regions were selected for empirical analysis so that suggestions for optimization could be put forward.

RESULTS

The structural equation model consisted of three parts: organization structure, executive process, and effect. The factor loading of the three indicators exceeded 0.5, indicating that this model complied with the preliminary fit criteria. In the organizational structure, rules and regulations and resource investment accounted for a large proportion, indicating that they had a great impact on the effect. As for the executive process, the weight of the seven indicators were similar, and they accounted for a large proportion, indicating that each indicator had a non-negligible impact on the effect. The "p" of all the three hypothesizes was less than .01, especially the "p" of hypothesis 3 was less than .001, indicating that the structure and process of NEMP affected the accessibility of the essential medicines, and three components of the model were positively correlated.

LIMITATIONS

Some errors may exist in achieving appropriate expert selection because of potential researcher bias in the Delphi approach. The results from only six provinces in China may not be generalized nationwide.

CONCLUSION

The structural indicators and process indicators have a significant impact on outcome indicators, and they also have correlations. That is, the formulation and implementation of the national drug policy and related supporting measures play an important role in improving the accessibility of essential medicines.

Comparison of the Factor Structure of the Patient Health Questionnaire for Somatic Symptoms (PHQ-15) in Germany, the Netherlands, and China. A Transcultural Structural Equation Modeling (SEM) Study

Background: Persistent somatic symptoms are associated with psychological distress, impaired function, and medical help-seeking behavior. The Patient Health Questionnaire (PHQ)-15 is used as a screening instrument for somatization and as a monitoring instrument for somatic symptom severity. A bifactorial model has been described, with one general factor and four orthogonal specific symptom factors. The objective of the present study was to assess and to clarify the factor structure of the PHQ-15 within and between different countries in Western Europe and China. Method: Cross-sectional secondary data analysis performed in three patient data samples from two Western European countries (Germany N = 2,517, the Netherlands N = 456) and from China (N = 1,329). Confirmatory factor analyses (CFA), and structural equation modeling (SEM) analysis were performed. Results: The general factor is found in every sample. However, although the outcomes of the PHQ-15 estimate severity of somatic symptoms in different facets, these subscales may have different meanings in the European and Chinese setting. Replication of the factorial structure was possible in the German and Dutch datasets but not in the dataset from China. For the Chinese dataset, a bifactorial model with a different structure for the cardiopulmonary factor is suggested. The PHQ-15 could discern somatization from anxiety and depression within the three samples. Conclusion: The PHQ-15 is a valid questionnaire that can discern somatization from anxiety and depression within different cultures like Europe or China. It can be fitted to a bifactorial model for categorical data, however, the model can only be recommended for use of the general factor. Application of the orthogonal subscales in non-European samples is not corroborated by the results. The differences cannot be ascribed to differences in health care settings or by differences in concomitant depression or anxiety but instead, a cultural factor involving concepts of disease may play a role in this as they may play a role in the translation of the questionnaire. Further research is needed to explore this, and replication studies are needed regarding the factorial structure of the PHQ-15 in China.

A Cross-Lagged Panel Analysis of Psychometric Intelligence and Achievement in Reading and Math

A cross-lagged panel analysis of Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) intelligence test scores and reading and math achievement test scores of 337 students twice assessed for special education eligibility across a test-retest interval of 2.85 years was conducted. General intelligence (g) was loaded by the four WISC-IV factor index scores whereas reading and math were composite scores. After confirming measurement invariance, it was found that g, reading, and math were stable across time and synchronously correlated. The cross-lagged paths from g at time 1 to reading and math at time 2 (0.26 and 0.39, respectively) were both significantly greater than zero whereas the paths from reading and math at time 1 to g at time 2 (0.03 and 0.23, respectively) were not statistically significant. Given this pattern of relationships and extant research on the correlates of general intelligence, it was tentatively inferred that general intelligence was the temporal precursor to reading and math achievement.

Progressive Bidirectional Age-Related Changes in Default Mode Network Effective Connectivity across Six Decades

The default mode network (DMN) is a set of regions that is tonically engaged during the resting state and exhibits task-related deactivation that is readily reproducible across a wide range of paradigms and modalities. The DMN has been implicated in numerous disorders of cognition and, in particular, in disorders exhibiting age-related cognitive decline. Despite these observations, investigations of the DMN in normal aging are scant. Here, we used blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) acquired during rest to investigate age-related changes in functional connectivity of the DMN in 120 healthy normal volunteers comprising six, 20-subject, decade cohorts (from 20–29 to 70–79). Structural equation modeling (SEM) was used to assess age-related changes in inter-regional connectivity within the DMN. SEM was applied both using a previously published, meta-analytically derived, node-and-edge model, and using exploratory modeling searching for connections that optimized model fit improvement. Although the two models were highly similar (only 3 of 13 paths differed), the sample demonstrated significantly better fit with the exploratory model. For this reason, the exploratory model was used to assess age-related changes across the decade cohorts. Progressive, highly significant changes in path weights were found in 8 (of 13) paths: four rising, and four falling (most changes were significant by the third or fourth decade). In all cases, rising paths and falling paths projected in pairs onto the same nodes, suggesting compensatory increases associated with age-related decreases. This study demonstrates that age-related changes in DMN physiology (inter-regional connectivity) are bidirectional, progressive, of early onset and part of normal aging.

Applying Electronic Medical Records in Health Care: Physicians' Perspective

BACKGROUND

In order to fulfill comprehensive interoperability and recognize the electronic medical records (EMRs') benefits, physicians' attitudes toward using and applying EMR must be recognized.

OBJECTIVES

The purpose of this study was to present an integrated model of applying EMRs by physicians.

METHODS

This was a cross sectional study in which a sample of 330 physicians working in hospitals affiliated to the Tehran University of medical sciences (TUMS) was selected. Physicians' attitudes toward using and accepting EMR in health care have been analyzed by an integrated model of two classical theories i.e. technology acceptance model (TAM) and diffusion of innovation (DOI). The model was tested using an empirical survey. The final model was tested by structural equation modeling (SEM) and represented by Analysis of Moment Structures (AMOS).

RESULTS

The results suggest that the hybrid model explains about 43 percent of the variance of using and accepting of EMRs (R2=0.43). The findings also evidenced that Perceived Usefulness (PU), Perceived Ease of Use (PEOU), Relative Advantage, Compatibility, Complicatedness and Trainability have direct and significant effect on physicians' attitudes toward using and accepting EMRs. But concerning observeability, significant path coefficient was not reported.

CONCLUSIONS

The integrated model supplies purposeful intuition for elucidates and anticipates of physicians' behaviors in EMRs adoption. The study identified six relevant factors that affect using and applying EMRs that should be subsequently the major concern of health organizations and health policy makers.

Continuous Glucose Monitoring in Type 1 Diabetes

BACKGROUND

Continuous glucose monitoring (CGM) patient systems have been shown to improve diabetes self-treatment when used consistently. The meaningful integration of this technology into everyday life, however, can vary greatly among CGM users and not all people with diabetes use CGM to its full potential. To address this issue, the study pursued 2 aims: first, to identify patient characteristics that underlie the acceptance of CGM in people with type 1 diabetes and, second, to examine the effects of different levels of experience with CGM use.

METHODS

Guided by a model based on the technology acceptance model (TAM), structural equation modeling (SEM) was employed to model the patient characteristics as predictors of CGM acceptance. In all, 111 participants (60.4% female, mean = 37.6 years, SD = 11.2) participated in a web-based survey; 40 were current CGM users, 18 were former users and 53 had no experience with CGM systems.

RESULTS

In general, participants evaluated CGM positively; however, the feeling of information overload represented a major barrier to the sustained use of CGM, while perceptions of usefulness and ease of use constituted incentives for using this technology. Moreover, patients without CGM experience imagined more information overload than current users reported. Current users showed more intention to use CGM than former users.

CONCLUSION

This study highlights the importance of CGM user experience for the effective use of this technology.

English language usage pattern in China mainland doctors: AME survey-001 initial analysis results

PURPOSE

English is the most widely used language in medical community worldwide. Till now there is no study yet on how English language is being used among mainland Chinese doctors. The present survey aimed to address this question.

METHODS

An online cross-sectional survey was carried out during the period of 23 Oct 2014 to 13 November 2014, totaling 22 days. This survey was conducted on the platform provided by DXY (www.dxy.cn), which is the largest medical and paramedical related website in China with registered medical doctor users of slightly more than one million. E-mails were sent to all DXY registered users to invite them to participate the survey which lasts approximately five-minute. The questionnaire included three major aspects: (I) the demographic characteristics of participants; (II) English reading pattern; and (III) paper publishing experience in international journals. To accommodate the complexity of relationships among variables, structural equation modeling (SEM) was employed to build the model.

RESULTS

In total 1,663 DXY users completed the survey, which counted for ≈1% of the total registered medical doctor users. There were more participants from relatively economically developed eastern coast areas. The age of participants was 33.6±7.4 years. There were 910 respondents from teaching hospitals (54.72%), followed by tertiary care hospitals (class-III hospital, 22.37%). Mainland Chinese doctors were more likely to consult medical materials in Chinese (63.5%) when they encounter clinical difficulties. Participants who were able to list English journals of their own specialty up to four were 44.02% for 0, 13.77% for one journal, 13.89% for two journals, 9.26% for three journals, and 19.06% for four journals. Most participants (82.86%) have read at least one English paper or one professional book in English, while 17.14% responded they never read a single English paper or professorial book in English. About 30.42% participants published at least one paper in English journals, and approximately half of them require professional English editing service.

CONCLUSIONS

This limited survey shows Mainland Chinese doctors are more likely to use Chinese medical materials. Overall their familiarity with international English journals is relatively low. Improving English education at the undergraduate and post-graduate levels is recommended.

Measurement bias detection with Kronecker product restricted models for multivariate longitudinal data: an illustration with health-related quality of life data from thirteen measurement occasions

Highlights

Longitudinal measurement invariance is usually investigated with a longitudinal factor model (LFM). However, with multiple measurement occasions, the number of parameters to be estimated increases with a multiple of the number of measurement occasions. To guard against too low ratios of numbers of subjects and numbers of parameters, we can use Kronecker product restrictions to model the multivariate longitudinal structure of the data. These restrictions can be imposed on all parameter matrices, including measurement invariance restrictions on factor loadings and intercepts. The resulting models are parsimonious and have attractive interpretation, but require different methods for the investigation of measurement bias. Specifically, additional parameter matrices are introduced to accommodate possible violations of measurement invariance. These additional matrices consist of measurement bias parameters that are either fixed at zero or free to be estimated. In cases of measurement bias, it is also possible to model the bias over time, e.g., with linear or non-linear curves. Measurement bias detection with Kronecker product restricted models will be illustrated with multivariate longitudinal data from 682 bone metastasis patients whose health-related quality of life (HRQL) was measured at 13 consecutive weeks.