Espacios. Vol. 36 (Nº 06) Año 2015. Pág. 7

Effect and relationship between quality of life and quality of life in the work through the use of the multivaried analysis

Efeito e relação entre a qualidade de vida e a qualidade de vida no trabalho através da utilização de análise multivariada

Luciana da Silva TIMOSSI 1; Márcia Bento MOREIRA 2; Kleverton KRINSKI 3; Guataçara dos SANTOS JUNIOR 4; Antonio Carlos DE FRANCISCO 5

Recibido: 24/10/14 • Aprobado: 14/12/14

Contenido

1 Introduction
2 Methodological
3 Results and discussion
4 Conclusion
5 References

1. Introduction

This study presents a differentiated proposal of correlation analysis between the Quality of Life (QL) and the Quality of Life in Work (QLW) through the use of the multivaried statistics analysis, focusing the questions between the man and his work, mainly with focus in the possible relationship between the Quality of Life (QL) and the Quality of Life in Work (QLW).

The first concepts on QL were worried initially about material questions in the life of the individuals as obtained wage, goods, success in the professional area, that is, prioritized external factors. Currently, a differentiated approach related to the QL of the people is perceived, pointing a valuation of inherent factors to the human being as satisfaction degree, either professional accomplishment as personal, good relationship with the society and access to the culture and to the leisure as real examples of welfare.

In the area of Health and Medicine the evaluation of the QL is generally related to the inquiry of pathologies and their consequences for the health and the life of the individual. The QL Fleck, et. Al (1999) involves "similar concepts, centered in the subjective evaluation of the patient, but necessarily related to the impact of the health state on the capacity of the individual of living fully". In the other hand in the industrial productive area, the concern in evaluating QL and/or QLW appeared more recently. In Brazil dissertations and theses in the area of Administration regarding the QLW are found since 1989 and since 1996 in the area of Engineering of Production.

The inquiry of the QL when applied to the Engineering of Production area can allow a better understanding about the habits, the style of life, the health and the necessities of the collaborators of companies and industries. This because in a general way the QL is intimately related to factors as: health state, longevity, satisfaction in the work, wage, leisure, familiar relations, disposal, pleasure and spirituality of the individuals, being this concept different from person to person and changing throughout the life (NAHAS, 2006).

The QL can also be considered as Ferris (2006) the result of two endogenous and exogenous forces. "The endogenous ones include mental, emotional forces and physiological answers of the individual to his/her life. The exogenous forces include the social, cultural and psychological social structure, and influences of the social environment, that affect the individual, group and the community".

In the same way that the evaluation of the QL involves multi-factors, the QLW inquiry is mainly worried about the satisfaction of the collaborator in relation to factors as: wage; security; health in work; physical conditions of work which reduce to the minimum the risk of occupational illnesses and industrial accidents; development of the capacities and multiple abilities; autonomy; information; professional growth; social integration and space of life in work and out of it. The QLW can be understood as França e Zaima (2002) a "set of the actions of a company which involves the implantation of improvements and managemental, technological and structural innovations in the work environment". Also including wide aspects of the work environment that affect the collaborator in his/her health and his/her performance (COLE, et. al, 2005).

It is known that the QL and the QLW are the aim of innumerable discussions. However, these subjects deserve a reflection under the perspective that the human being and the organizations/companies are in constant interaction and movement. It is presupposed that to analyze the QL or QLW separately one of the other generates certain inconsistency, because in this in case there is a separation of the human being, sometimes seen as a person sometimes as a worker. As justification for a wider analysis of the influences exchanges between QL and QLW, there is the necessity at a first moment to verify in a consistent form there is really a significant general correlation between QL and QLW.

Commonly in the studies that involve QL and QLW, it is not used multivaried statistical techniques in the treatment and analysis of the data. As an example it can be observed the following accomplished studies (FLECK, et.al, 1999; COLE, et. al, 2005). When dealing with correlations analysis, the univaried statistics, frequently used to investigate a possible correlation, does not seem to be the best alternative. This is observed by the fact of not taking in consideration all the involved variable at the same time to form a conclusion. When this occurs, is not possible to optimize the extraction of information and, it is possible to obtain misleading conclusions or at least not so complete. Because of this reason, the verification of a possible significant correlation between QL and QLW is necessary to use a method that contemplates all the variable simultaneously, that is, a more consistent statistical method. When the variables in study are analyzed separately many information are lost about the study phenomenon (MINGOTI, 2007). The "Multivaried Statistic consists on a set of statistical methods used in situations in which some variables are evaluated simultaneously".

In this way, this work has as its main objective to present a differentiated proposal of correlation analysis between QL and QLW through the use of the multivaried statistics analysis. The application of this proposal can lead to possible findings, unknown up to the moment, about correlations between the QL and the QLW in collaborators. In this context, this work offers to the managers or researchers better subsidies about a possible significant correlation between QL and QLW. With the problem of the correlation between QL and QLW being solved in a consistent form, greater and better clarifications for the questions that involve QL and QLW can be analyzed with bigger security.

The proposal emergence

Some authors are already defending the idea of relation between the QL and the QLW. The table below presents the authors and their ranks regarding this subject.

Table 1. Authors and their processions about the relation between the QL and the QLW

According to the authors cited previously, it is perceived the importance to visualize, to observe, to understand and also to investigate the individual in a wider form, and not in a segmented form, evaluating sometimes as worker sometimes as subject. In such a way, it can then be assumed that a dichotomy exists when only one evaluation is carried out. Where the intention in analyzing and relating the QL added to the QLW objective something bigger, the perspective to offer to the researcher or the manager the chance to visualize the person as a whole. This can contribute a lot to answer and to clarify doubts and questionings that commonly appear when people are evaluated, which possess individual and intrinsic characteristics.

2. Methodological procedures for evaluation of the correlation between quality of life and quality of life in work

Proposal characterization

The methodology proposed in this work was developed and tested in collaborators of a public organization, situated in Paraná - Brazil, with performance area in the control of the collection tax of the Union and customs control of the Brazilian importations and exportations. A measurement system was applied in factors as: opinions, values and attitudes related to the QL and the QLW, quantifying them in measurable numerical information for posterior multivaried analysis. In all 14 variables had been analyzed (6 QL domains and QLW 8 criteria) with a sample of 106 collaborators. For the analysis the obtained QL and QLW data had been organized in a data matrix.

In sequence it is important to highlight that in the application of this proposal the definition of the analysis levels and the number of cases where it is intended to explore is a relevant point. In this way, multiple levels of analysis in multiple cases can be used, this allow as it suggests [16]"comparisons either in the horizontal plan  (among different cases in the same reality level) or vertical (among different levels of reality)". It is done therefore a transversal cut, a prompt study of the QL and the QLW and their phenomena involved in a specific period of the collaborators life, as it was a picture of the moment and lived experiences. The evaluation can be carried out in any work organization, private or public, since there is fidelity about the methodological procedures presented in this proposal.

Procedure of the multivaried correlation analysis

In the previously displayed context, it was searched to verify a possible existence of significant general correlation among the 6 domains of WHOQOL- 100 instruments: physical, psychological, independence level, social relations, environment, and spirituality/personal beliefs, and the 8 criteria of the instrument that evaluates the QLW [17] fair and adequate compensation, work conditions, use and development of capacities, chance of growth and security, social integration in the organization, constitutionalism, the work and the total space of life, social relevance of the work in the life. Soon, it was worked with 14 variables (6 QL domains and 8 QLW criteria). To exemplify the proposed analysis it was worked with a sample size n = 106, that is, 106 collaborators had been evaluated. Therefore, the data to be analyzed consist in a matrix of dimension 106 x 14. In this way, it was possible to construct a hypotheses test for the evaluation of the global correlation matrix. The suggested hypothesis test is the Bartlet (RENCHER, 2002; JOBSON, 1996). The hypothesis test is formulated in the following way:

In the expression (1), I p x p is the identity matrix and Pp x p is the matrix of theoretical correlation of the p - variable involved in the study. With the null hypothesis it is FOCUSED to test if the p - variable in study they are independent, in other words, if the covariance's matrix of the data matrix or sample matrix is diagonal. This is justified by the fact that in case of the normal distribution, correlation equal to zero implies in independence of the p variable in study. Therefore, to exist a significant multivaried correlation among the variables in study, the null hypothesis must be rejected.

 It is considered the test statistics T defined by:

where ln (.) denotes the neperian logarithm function and , withare the auto values or proper values of the sample correlation matrix R p x p. Considering n (sample size) big, the statistic of test given by the equation (2) has a distribution approximately qui-square with  degrees of freedom. Therefore it is rejected null hypothesis if the value observed for the statistic of test T is bigger or equal to the critical value gotten from the qui-square distribution for the significance level adopted for the test.
Any symmetrical matrix, what is the case of the sample correlation matrix, can be decomposed in auto values or proper valuesand auto vectors or eingenvectors. This decomposition is called spectral decomposition. The spectral decomposition of the matrix of the correlation matrix is represented by:

 where M is the orthogonal matrix whose columns are eingenvectors of  and    is the diagonal matrix formed by the proper values of . Among the proper values of  exists the following relation. Therefore, the spectral decomposition of  is represented by the equation (4) to follow:

The proper values  Î  of the  matrix and the eingenvectors  Î , are solutions of the equation   the proper values and eingenvectors of R are exactly those that satisfy the equation (5). Thus, the only way to obtain eingenvectors , with m ¹ 0 is to have:

Imposing the condition represented by the equation (6), it is determined, firstly, the proper values  which satisfy the equation (5) and, after, the eingenvectors associated to them.

Developing the equation (6), it is had

That is,                                                                                                                                                                        

P(l) is called R matrix characteristic polynomial and the set of all the proper values of the R matrix, is called R specter.
More detailed information about the spectral decomposition theorem can be obtained in (JOHNSON, WICHERN, 1998; BRONSON, 1993; DEJOURS, 1989).

3. Results and proposal discussion

According to the 14 analyzed variables, being (6 QL domains and 8 QLW criteria) with a sample of 106 collaborators. The data matrix was definite as: A 106 x 14, that is, 106 x 14 dimension. In the sequence the sample correlation matrix was calculated, which was definite as being R 14 x 14. Considering these gotten data, the hypothesis test proposed by the equation 1 was formulated in accordance with the equation (3) to follow:

To calculate the statistics of test given by the equation (2) it was used  and the 14 auto values or proper values () corresponding to the 14 variables are placed in increasing order in the following matrix:

Soon, from the calculation of the statistics of test given by the equation (2) it was obtained . The critical value obtained from the qui-square distribution with significance level equal to 0,05 and 91 degrees of freedom is 114,3. As the obtained value 1096,2 for statistic of test is bigger than the critical value 114,3, the null hypothesis is rejected. Therefore, it is concluded that the variables in study (domains and criteria) are not independent, that is, there is a significant correlation among them.

The result obtained in the correlation multivaried analysis between QL and QLW, indicates that relevant aspects can now be discussed in a more structured and secure way. As an example, the inquiry about the specific correlation among the QL domains and the QLW criteria. Although many studies approach the QL, few have based in the worker health in a wider context, also taking into consideration the QLW. Defending that the health, either in the work or general, cannot be seen as something static that once reached time is constant, Dejours, (1989) and that the complete and perfect physical, mental and social welfare does not exist, is something that the human being is always pursuing.

In a similar way that the man is inserted in a continuous process of change in search of the "healthful balance", the companies are also in this same context, developing strategies to follow the increase of the complexity of the market relations. The current industrial scene demands that the work organizations innovate all the time, either in the quality, the technology, the implantation of programs directed toward the health and security of their professionals and in the respect to the environment norms. The productive processes are constantly demanding innovations. Thus, some companies had started to notice that changing the attention focus to the individuals that compose the organization can be a good enterprise strategy. Inside of this, the inquiry of QL together with the QLW can be fit as one of the possibilities or strategies of the companies in directing a bigger attention to the questions related to the valuation of the human capital.

Studying the relations between work and health it is perceived that what matters in the work in relation to the mental and physical balance is the work organization (DEJOURS, 1989). It is highlighted the importance of the QLW inquiry approaching physical work questions as: environment, illumination, load, repetition, and with equal importance the organizational questions: relationship, positions, wage compensation, professional recognition. In the current competitive environment the companies need healthful, prepared and motivated collaborators for the competition. In this direction, the company can perform an important role in the health construction of its collaborator through the QL inquiry added to the QLW inquiry, therefore the results of these evaluations will contribute:

- To direct in a less intuitive way the points and factors that the company can invest to guarantee to its collaborator a better QL and QLW.

- To offer opportunities and ways of awareness so that the change of life style can occur.

- To base in consistent way the investments on Worker Health Promotion Programs, ministering the necessities of the employees in a more efficient way.

- To a Better organizational performance: the knowledge of the company about the factors that are present in the life of its collaborators and that causes insatisfaction for them, can supply important subsidies so that the organization can act. With this, this action will be coherent in the decisions taking, contributing to an improvement in the life of these people, what can consequently lead to a better performance of the organization.

Still this analysis reaches the necessity to contribute for the evolution of the science inside the health area of the worker, having as leading question, the accompaniment and development of action which always try to reduce to the maximum the difficulties and constraints imposed to the collaborators, either in the physical, cognitive or psychic area.

4. Conclusion

Through this study it was possible to present a differentiated proposal of QL and QLW data analysis, using the multivaried statistic related to the existing correlation between them. A differential present in this work is the use of the multivaried analysis to justify the existing correlation between QL and QLW. The method proposed for the correlation analysis between QL and QLW meet the necessity of systemizing a procedure for it.

Thus, a multivaried correlation between QL and QLW is defined in a consistent way, without leaving doubts about the obtained result. It is highlighted that the method proposed here for the correlation analysis between QL and QLW can perfectly be used in other situations, that is, in other applications. However, some cares with the method application deserve a bigger attention. It is important to highlight that the quality of the result depends, on the care in the data collection by the researcher. However, an any-situation-valid-rule does not exist. But an important point is related to the sample size.

Because of the fact that to analyze the considered problem, it is necessary to estimate  parameters between variances and co-variances, there is the necessity to use common sense in the choice of the sample size and in the choice of the variables number to be studied. This is because the need to have a sample of superior size to the number of studied parameters. The quality of the obtained result will depend on this care. The results had indicated the possibility to find among the QL and QLW variables (domains and criteria) dependence or independence in a general way. It was perceived then that the tools pointed in this study are capable not only to evaluate the QL and the QLW in companies and industries, but in the most different types of working organizations, either public or private, contemplating the innumerable variables in distinct organizational contexts. Its use in set extends the dimension and the understanding about the relation between QL and QLW, being this knowledge important and necessary to structuralize health promotion and orientation programs inside and outside of the work. It can also be verified that the exploration of the QL and QLW instruments, added with the multivaried correlation, being statistically proved can offer the possibility of intervention in QL and/or QLW in a less intuitive way, where the found results are product of a wider approach analysis, breaking the existing current dichotomy.

This strengthens the idea that the man cannot be seen in a fragmented form or being observed as an individual inside of the work and another out of it. In such a way, obtaining value 1096,2 of the test statistics bigger than the critical value 114,3, it is concluded that the variables in study, QL and QLW, present significant correlation, being the 14 analyzed variables (QL 6 domains and 8 QLW criteria) related. These can affect each other either in a maleficent or healthful form.

Thanks: The authors thank the support granted for the Staff Perfectioning Coordination of Superior Level (Capes) - Brazil, through the financial support received in order to elaborate the research.

References:

Bronson, R. (1993). Matrizes. Lisboa: McGraw-Hill.

Cole, D. C.; Robson, L. S.; Charles, L. L.; McGuire, W.; Sicotee, C.; Champagne, F. (2005). Quality of working life indicators in Canadian health care organizations: a tool for healthy, health care workplaces? Occupational Medicine, n. 55, p. 54 – 59.

Cooper, C. L. (2005). A natureza mutante do trabalho: o novo contrato psicológico e os estressores associados. In: ROSSI, A. M.; PERREWÉ, P. L.; SAUTER, S. (Org.) Stress e qualidade de vida no trabalho: perspectivas atuais da saúde ocupacional. São Paulo: Atlas.

Danna, K.; Griffin, R. W. (1999). Health and well-being in the workplace: a review and synthesis of the literature. Journal of Management. v.25, n.3, p.357-384.

Dejours, C. (1989). Por um novo conceito de saúde. Revista Brasileira de Saúde Ocupacional. São Paulo, v.14, n.54, p. 7-14.

Ferriss, A. L. (2006). A Theory of Social Structure and the Quality of Life. Applied Research in Quality of Life, n. 01, p. 117-123.

Fleck, M. P. A., et. al. (1999). Desenvolvimento da versão em português do instrumento de avaliação da qualidade de vida da OMS (WHOQOL-100). Revista Brasileira de Psiquiatria, v. 21, n.1, p.19-28.

França, A. C. L.; Zaima, G. (2002). Gestão da qualidade de vida no trabalho – GQLW. In: Manual de gestão de pessoas e equipes: estratégias e tendências. São Paulo: Gente.

Grandjean, E. (1998). Manual de ergonomia: adaptando o trabalho ao homem. 4. ed. Porto Alegre: Bookman.

Jobson, J. D. (1996). Applied multivariate data analysis. v. I e II. New York: Springer Verlag.

Johnson, R. A.; Wichern, D. W. (1998). Applied Multivariate Statistical Analysis. 4. ed. New Jersey.

Loscocco, K. A. & Roschelle, A. R. (1991). Influences on the Quality of Work and Nonwork life: Two Decades in Review. Journal of Vocational Behavior, 39, p. 182-225.

Mingoti, S. A. (2007). Análise de dados através de métodos de estatística multivariada: uma abordagem aplicada. Belo Horizonte: Editora UFMG.

Nahas, M. V. (2006). Atividade física, saúde e qualidade de vida: conceitos e sugestões para um estilo de vida ativo. 4. ed. Londrina: Midiograf.

Rencher, A. C. (2002). Methods of multivariate analysis. New York: John Wiley.

Vasconcelos, E. M. (2002). Complexidade e pesquisa interdisciplinar: epistemologia e metodologia operativa. Petrópolis: Vozes.

Walton, R. E. (1975). Criteria for quality of work life. In: DAVIS, L. E.; et al. Quality of working life: problems, projects and the state of the art. New York: Macmillian, v.1, p. 91-104.

1. Doutora, Professora do Programa de Pós Graduação Ciências da Saúde e Biológica na Universidade Federal do Vale do São Francisco – UNIVASF, Brasil. E-mail: luciana.silva@univasf.edu.br
2. Doutora, Professora do Programa de Pós Graduação Ciências da Saúde e Biológica na Universidade Federal do Vale do São Francisco – UNIVASF, Brasil. E-mail: márcia.moreira@univasf.edu.br
3. Doutor, Professor na Universidade Federal do Vale do São Francisco – UNIVASF, Brasil. E-mail: kleverton.krinski@univasf.edu.br
4. Doutor, Professor do Programa de Pós-Graduação em Engenharia de Produção da Universidade Tecnológica Federal do Paraná – UTFPR, Ponta Grossa, Paraná, Brasil. E-mail: guata39@gmail.com
5. Doutor, Professor do Programa de Pós-Graduação em Engenharia de Produção da Universidade Tecnológica Federal do Paraná – UTFPR, Ponta Grossa, Paraná, Brasil. E-mail: acfrancisco@gmail.com