Os Impactos das Avaliações do Cuidado de Saúde no Bem-Estar da Baixa Renda

Lilian Tellini

Universidade Nove de Julho, Programa de Pós Graduação em Administração, São Paulo, SP, Brasil

Andre Torres Urdan

Universidade Nove de Julho, Programa de Pós Graduação em Administração, São Paulo, SP, Brasil

Sonia Francisca Monken

Universidade Nove de Julho, Programa de Pós Graduação em Administração, São Paulo, SP, Brasil

Flavio Santino Bizarrias

Universidade Nove de Julho, Programa de Pós Graduação em Administração, São Paulo, SP, Brasil

Marcelo Moll Brandão

Universidade Federal do Espirito Santo, Programa de Pós-graduação em Administração, Vítória, ES, Brasil

Conflict of Interest

The authors have stated that there is no conflict of interest.

Plagiarism Check

The RAC maintains the practice of submitting all documents approved for publication to the plagiarism check, using specific tools, e.g.: iThenticate.

Supplementary Material

All data and materials have been made publicly available through the Mendeley platform and can be accessed at: Tellini, Profa Lilian; Urdan, André; Monken, Sonia; Bizarrias, Flavio; Brandão, Marcelo (2019), “Data for: "The Impact of Health Care Services Evaluations on Well-Being of Low-Incomers" published by RAC-Revista de Administração Contemporânea”, Mendeley Data, v1. Retrieved from: http://dx.doi.org/10.17632/gn2jvckszx.1

Indicator	Purpose	Criteria
AVE	Convergent validity	AVE > 0.50
Cross loads	Discriminant validity	Higher load values in the original latent variables than in others.
Fornell and Larcker Criteria	Discriminant validity	The square roots of the AVEs larger than the correlations of the constructs.
Cronbach’s Alpha and Composite Reliability	Reliability	AC > 0.70 CC > 0.70
Student t test	Evaluates the significance of the correlations and regressions	t ≥ 1.96 or 5% (t ≥ 1.79, p ≤ 0.05)
Pearson Determination Coefficient (R²)	Evaluate the portion of the variance of an endogenous variable that is explained by the structural model.	In social and behavioral sciences, 2%<R2£13% is a small effect, 13<R2£26% is moderate, 26%<R²is large.
Effect size (f²) or Cohen indicator	Evaluates how useful each construct is for the adjustment of the model	Values of 0.02, 0.15 and 0.35 are considered small, medium and large, respectively.
Predictive Validity (Q²) or Stone-Geisser Indicator	Evaluates the accuracy of the adjusted model	Q² > 0
Goodness of Fit (GoF)	Global quality indicator of the adjusted model	GoF>0.36 (suitable)
Path coefficient (Г)	Evaluation of causal relationships	Interpretation of the values in light of theory

Construct	Well-being	Perceived Quality	Perceived Sacrifice	Satisfaction	Perceived Value
Well-being	1	-	-	-	-
Perceived Quality	0.6239	1	-	-	-
Perceived Sacrifice	0.4067	0.4615	1	-	-
Satisfaction	0.5926	0.6788	0.3531	1	-
Perceived Value	0.5747	0.6273	0.5895	0.483	1

Construct	AVE	Composite Reliability	Cronbach’s Alpha	R²
Well-being	0.631	0.895	0.854	0.351
Perceived Quality	0.608	0.933	0.919	0.000
Perceived Sacrifice	0.744	0.897	0.826	0.000
Satisfaction	0.711	0.925	0.898	0.466
Perceived Value	0.619	0.829	0.712	0.508

Hypo-thesis	Path	Original coefficient	Mean coefficient of 500 resamples	Standard Error	T test	p-value	Result
H1	Perceived Sacrifice → (−) Perceived Value	0.381	0.382	0.07	5.418	0.001	not supported
H2	Perceived Value → (+) Satisfaction	0.094	0.098	0.073	1.297	0.196	not supported
H3	Perceived Quality → (+) Perceived Value	0.451	0.453	0.062	7.331	0.001	supported
H4	Perceived Quality → (+) Satisfaction	0.62	0.616	0.067	9.193	0.001	supported
H5	Satisfaction → (+) Well-being	0.593	0.596	0.044	13.483	0.001	supported

Brasil