scholarly journals The influence of culture on care receivers’ satisfaction and aggressive tendencies in the emergency department

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0256513
Author(s):  
Alon Lisak ◽  
Dorit Efrat-Treister ◽  
Ella Glikson ◽  
Vladimir Zeldetz ◽  
Dan Schwarzfuchs

Introduction Reducing aggressive tendencies among care receivers in the emergency department has great economic and psychological benefits for care receivers, staff, and health care organizations. In a study conducted in a large multicultural hospital emergency department, we examined how cultural factors relating to ethnicity interact to enhance care receivers’ satisfaction and reduce their aggressive tendencies. Specifically, we explored how care receivers’ cultural affiliation, individual cultural characteristics, and the cultural situational setting interact to increase care receivers’ satisfaction and reduce their aggressive tendencies. Method Data were collected using survey responses from 214 care receivers. We use structural equation models and the bootstrap method to analyze the data. Results Care receivers’ openness to diversity (an individual cultural characteristic) was positively related to their satisfaction that was associated with lower aggressive tendencies, only when they were affiliated with a cultural minority group and when the cultural situational setting included language accessibility. Conclusion Our results demonstrate that cultural affiliation, individual cultural characteristics, and cultural situational setting can affect care receivers’ satisfaction and aggressive tendencies in a multicultural emergency department context. In particular, high cultural openness of care receivers, and making information accessible in their native language, increased satisfaction and reduced aggressive tendencies among cultural minority care receivers in our study.

2016 ◽  
Vol 76 (6) ◽  
pp. 889-911 ◽  
Author(s):  
Matthew J. Valente ◽  
Oscar Gonzalez ◽  
Milica Miočević ◽  
David P. MacKinnon

Methods to assess the significance of mediated effects in education and the social sciences are well studied and fall into two categories: single sample methods and computer-intensive methods. A popular single sample method to detect the significance of the mediated effect is the test of joint significance, and a popular computer-intensive method to detect the significance of the mediated effect is the bias-corrected bootstrap method. Both these methods are used for testing the significance of mediated effects in structural equation models (SEMs). A recent study by Leth-Steensen and Gallitto 2016 provided evidence that the test of joint significance was more powerful than the bias-corrected bootstrap method for detecting mediated effects in SEMs, which is inconsistent with previous research on the topic. The goal of this article was to investigate this surprising result and describe two issues related to testing the significance of mediated effects in SEMs which explain the inconsistent results regarding the power of the test of joint significance and the bias-corrected bootstrap found by Leth-Steensen and Gallitto 2016. The first issue was that the bias-corrected bootstrap method was conducted incorrectly. The bias-corrected bootstrap was used to estimate the standard error of the mediated effect as opposed to creating confidence intervals. The second issue was that the correlation between the path coefficients of the mediated effect was ignored as an important aspect of testing the significance of the mediated effect in SEMs. The results of the replication study confirmed prior research on testing the significance of mediated effects. That is, the bias-corrected bootstrap method was more powerful than the test of joint significance, and the bias-corrected bootstrap method had elevated Type 1 error rates in some cases. Additional methods for testing the significance of mediated effects in SEMs were considered and limitations and future directions were discussed.


2021 ◽  
Author(s):  
Thierry Devos ◽  
Kumar Yogeeswaran ◽  
Chris G Sibley

Using a nationally representative sample, the present research tested whether conceptions of national identity differentially predicted attitudes toward bicultural policies among New Zealanders of European, Māori, Asian, and Pacific descent. A series of multi-group structural equation models revealed that among members of the majority group and all minority groups, endorsement of a civic conception of national identity (i.e., respecting political institutions and laws) was related to opposition to resource policies, but such a relationship was especially strong among the majority group. By contrast, endorsement of an ethnic conception of national identity (i.e., having Māori or European ancestry) was related to support for resource and symbolic policies among minority group members, but to opposition to the same policies among the majority group. The present work documents that belonging to a majority vs. minority group moderates the relations between conceptions of national identity (civic vs. ethnic) and support or opposition to specific bicultural policies. In addition, some elements of civic conceptions of national identity may legitimize inequalities rather than reduce them.


1997 ◽  
Vol 20 (2) ◽  
pp. 269-286 ◽  
Author(s):  
B. Corenblum ◽  
R. C. Annis ◽  
J. S. Tanaka

Levels of cognitive development and perceived self-competencies have been shown to predict attitudes held by children in both minority and majority groups toward own-group members. Teacher appraisals may also influence children’s own-group attitudes by enforcing category-based expectancies and stereotypes about children’s group membership. To test this idea, White and Native Indian children in kindergarten, grades 1 and 2, answered recognition, similarity, and evaluation questions by pointing to pictures of Whites, Natives, and Blacks. Measures of children’s concrete operational thought and self-competency were obtained, as were classroom teacher ratings, of each child’s cognitive ability, peer acceptance, and physical development. Structural equation models indicated that teacher evaluations predicted White children’s, but not Native children’s own-group attitudes. Teacher ratings of Native children’s competencies did not predict minority children’s attitudes about themselves or own-group members. Implications of these findings for teacher expectancy effects and factors influencing teacher’s judgements of majority and minority group children were discussed.


2016 ◽  
Vol 21 (1) ◽  
pp. 193-213 ◽  
Author(s):  
Christopher T. Begeny ◽  
Yuen J. Huo

Two studies ( N = 1,048) examined how Blacks’, Asians’, and Latinos’ perceived value within their own ethnic group (ethnic intragroup status) shapes mental health (depression, anxiety, psychological distress). The proposed intragroup status and health (ISAH) model predicts that feeling valued among ethnic ingroup members has benefits for health, but also indirect costs. Costs arise because individuals who feel highly valued in their ethnic group see their ethnicity as more central to their self-concept; with stronger identity-centrality, individuals more frequently view daily social interactions through the “lens” of their ethnicity and ultimately perceive/experience more discrimination. Discrimination, in turn, adversely shapes mental health. Results of structural equation modeling supported these predictions across all groups in both studies. Thus, feeling valued in one’s minority group may be a double-edged sword for mental health. Overall, the ISAH model reveals how intragroup processes, when considered from an intergroup perspective, advance our understanding of minority mental health.


2000 ◽  
Vol 16 (1) ◽  
pp. 31-43 ◽  
Author(s):  
Claudio Barbaranelli ◽  
Gian Vittorio Caprara

Summary: The aim of the study is to assess the construct validity of two different measures of the Big Five, matching two “response modes” (phrase-questionnaire and list of adjectives) and two sources of information or raters (self-report and other ratings). Two-hundred subjects, equally divided in males and females, were administered the self-report versions of the Big Five Questionnaire (BFQ) and the Big Five Observer (BFO), a list of bipolar pairs of adjectives ( Caprara, Barbaranelli, & Borgogni, 1993 , 1994 ). Every subject was rated by six acquaintances, then aggregated by means of the same instruments used for the self-report, but worded in a third-person format. The multitrait-multimethod matrix derived from these measures was then analyzed via Structural Equation Models according to the criteria proposed by Widaman (1985) , Marsh (1989) , and Bagozzi (1994) . In particular, four different models were compared. While the global fit indexes of the models were only moderate, convergent and discriminant validities were clearly supported, and method and error variance were moderate or low.


2009 ◽  
Vol 14 (4) ◽  
pp. 363-371 ◽  
Author(s):  
Laura Borgogni ◽  
Silvia Dello Russo ◽  
Laura Petitta ◽  
Gary P. Latham

Employees (N = 170) of a City Hall in Italy were administered a questionnaire measuring collective efficacy (CE), perceptions of context (PoC), and organizational commitment (OC). Two facets of collective efficacy were identified, namely group and organizational. Structural equation models revealed that perceptions of top management display a stronger relationship with organizational collective efficacy, whereas employees’ perceptions of their colleagues and their direct superior are related to collective efficacy at the group level. Group collective efficacy had a stronger relationship with affective organizational commitment than did organizational collective efficacy. The theoretical significance of this study is in showing that CE is two-dimensional rather than unidimensional. The practical significance of this finding is that the PoC model provides a framework that public sector managers can use to increase the efficacy of the organization as a whole as well as the individual groups that compose it.


Methodology ◽  
2005 ◽  
Vol 1 (2) ◽  
pp. 81-85 ◽  
Author(s):  
Stefan C. Schmukle ◽  
Jochen Hardt

Abstract. Incremental fit indices (IFIs) are regularly used when assessing the fit of structural equation models. IFIs are based on the comparison of the fit of a target model with that of a null model. For maximum-likelihood estimation, IFIs are usually computed by using the χ2 statistics of the maximum-likelihood fitting function (ML-χ2). However, LISREL recently changed the computation of IFIs. Since version 8.52, IFIs reported by LISREL are based on the χ2 statistics of the reweighted least squares fitting function (RLS-χ2). Although both functions lead to the same maximum-likelihood parameter estimates, the two χ2 statistics reach different values. Because these differences are especially large for null models, IFIs are affected in particular. Consequently, RLS-χ2 based IFIs in combination with conventional cut-off values explored for ML-χ2 based IFIs may lead to a wrong acceptance of models. We demonstrate this point by a confirmatory factor analysis in a sample of 2449 subjects.


Methodology ◽  
2014 ◽  
Vol 10 (4) ◽  
pp. 138-152 ◽  
Author(s):  
Hsien-Yuan Hsu ◽  
Susan Troncoso Skidmore ◽  
Yan Li ◽  
Bruce Thompson

The purpose of the present paper was to evaluate the effect of constraining near-zero parameter cross-loadings to zero in the measurement component of a structural equation model. A Monte Carlo 3 × 5 × 2 simulation design was conducted (i.e., sample sizes of 200, 600, and 1,000; parameter cross-loadings of 0.07, 0.10, 0.13, 0.16, and 0.19 misspecified to be zero; and parameter path coefficients in the structural model of either 0.50 or 0.70). Results indicated that factor pattern coefficients and factor covariances were overestimated in measurement models when near-zero parameter cross-loadings constrained to zero were higher than 0.13 in the population. Moreover, the path coefficients between factors were misestimated when the near-zero parameter cross-loadings constrained to zero were noteworthy. Our results add to the literature detailing the importance of testing individual model specification decisions, and not simply evaluating omnibus model fit statistics.


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