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PurposeThe correlation between work and life satisfaction varies substantially across studies, suggesting that the strength of the relationship may depend on the studied population and its circumstances. The purpose of this paper is to assess the strength of the relationship in the context of Chile and the moderator effect of self-employment (SE), whether a worker is self-employed or on a salary.Design/methodology/approachBased on the idea that work plays a more central role in the life of a self-employed person than in that of a salaried worker, the authors hypothesized that the strength of the relationship between work and life satisfaction will be stronger for the former. The measures used in this study were part of a large questionnaire administered to investigate several characteristics of the Chilean population. The authors used multiple regression analysis to test the moderator effect of SE on the strength of the relationship between work satisfaction and life satisfaction.FindingsThe results from a national sample of 658 Chilean workers indicate that the relationship between work satisfaction and life satisfaction is positive. Furthermore, the relationship is stronger for self-employed workers than for salaried workers. The authors also found a small negative direct effect of SE on life satisfaction, which suggests that the self-employed might be, on average, less satisfied with their lives than their salaried counterparts.Originality/valueThe sample used in the current study was not only substantially larger in size but also more representative of the current workforce because it included both genders. Consequently, the results are more robust and generalizable.

RésuméLes auteurs examinent l'effet d'un programme visant à favoriser l'inclusion des personnes handicapées dans l'emploi sur l'absentéisme pour maladie et accident parmi les bénéficiaires. Après une évaluation qualitative des spécificités du programme, ils procèdent à une quasi‐expérience, en utilisant deux groupes témoins (non équivalent et sans traitement) et des séries chronologiques interrompues (2005–2012). L'analyse repose sur un modèle binomial négatif hiérarchique non imbriqué, avec une variable dépendante retardée. La comparaison entre les trois groupes (personnes handicapées, bénéficiaires ou non, et personnes valides) montre que les absences pour maladie sont sensiblement réduites chez les bénéficiaires. Pour les accidents, le recul est plus faiblement attesté.

ResumenSe investiga un programa empresarial de inclusión de personas con discapacidad con objeto de reducir el absentismo por enfermedad y por lesión. Tras observaciones de campo y entrevistas para determinar las características del programa, se aplicó un diseño cuasi experimental con dos grupos de control no equivalentes sin tratamiento y una serie temporal de 2005–2012. Mediante regresión binomial negativa jerárquica y una variable de resultado retardada, se compararon los datos de los trabajadores con discapacidad participantes con los no participantes y con los trabajadores sin discapacidad. Observamos una reducción de las ausencias por enfermedad entre los participantes, y también de las ausencias por lesión, aunque con resultados menos concluyentes.

AbstractThis article presents research on an organizational inclusion programme aiming to reduce absenteeism due to illness and injury among employees with disabilities. Qualitative fieldwork on the programme's characteristics was followed by a quasi‐experimental design with two control groups (non‐equivalent and no‐treatment) using abbreviated time series (2005–12). The data of employees with disabilities who participated in the programme were compared with those of non‐participants and of employees without disabilities, through a hierarchical non‐nested negative binomial regression with a lagged outcome variable. The authors find strong evidence of a reduction in absence due to illness among participant employees with disabilities, and somewhat weaker evidence of reduced absence due to injury.

AbstractThis article examines the subjective antecedents of life satisfaction of workers. Adopting a 'bottom-up' perspective, we assessed the unique influence that satisfaction with multiple life domains have on evaluative judgments of overall life satisfaction. Based on a nationwide sample of 530 Chilean workers, we simultaneously tested the effects of seven life domain satisfactions that have been consistently included in extant models of life satisfaction and subjective well-being. These were satisfaction with health, financial situation, social relationships, one's self-worth, leisure-time, family, and work. Having controlled for age and gender, results showed that satisfaction with one's financial situation was the dominant predictor of overall life satisfaction of workers, with a weight of .36. Satisfaction with family, work, and health had effects of .25, .14, and .14, respectively. Interestingly, satisfaction with one's self-worth, leisure-time, and social relationships did not have statistically significant effects on life satisfaction, although the first two showed t values near the critical value.

AbstractResearch shows that transformational leadership trainings can be beneficial even in highly hierarchical organizations. However, little is known about their enduring effects on such organizations when operating under social and political pressure. This study aims to evaluate a 3-month transformational leadership training programme in the Catalan police force, a programme that was designed and implemented in a period of extreme social and political upheaval. This study follows a quasi-experimental single group pre–post design, with three non-equivalent dependent variables as proxy counterfactuals. The training was delivered to police inspectors (N = 30). Leader assessments from subordinates (N = 129) were collected through the MLQ-5X questionnaire before the training (pre-test) and one year after the training (post-test). The quantitative analysis revealed that the training had a positive impact on four transformational leadership dimensions and in all leadership performance indicators. Some counter-theoretical results are discussed in the light of the social and political context of the study.

The aim of this article is to describe a method for relating two compositions which combines compositional data analysis and canonical correlation analysis (CCA), and to examine its main statistical properties. We use additive log-ratio (alr) transformation on both compositions and apply standard CCA to the transformed data. We show that canonical variates are themselves log-ratios and log-contrasts. The first pair of canonical variates can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition. The second pair can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition, under the restriction that they are uncorrelated with the first pair, and so on. Using properties from changes of basis, we prove that both canonical correlations and canonical variates are invariant to the choice of divisors in alr transformation. We show how to implement the analysis and interpret the results by means of an illustration from the social sciences field using data from Kolb's Learning Style Inventory and Boyatzis' Philosophical Orientation Questionnaire, which distribute a fixed total score among several learning modes and philosophical orientations ; The authors would like to acknowledge the support provided by Spanish Health Ministry Grant CB06/02/1002 funding the research group "Epidemiology and Public Health (CIBERESP)"; Catalan Autonomous Government Consolidated Research Group Grants 2014SGR551 and 2014SGR582 funding the research groups "Compositional and Spatial Data Analysis (COSDA)" and "Leadership Development Research Centre (GLEAD)"; Spanish Economy and Competitiveness Ministry grants MINECO/FEDER-EU MTM2015-65016-C2-1-R and EDU2015-68610-R funding the projects "Compositional Data Analysis and RElated meThOdS (CODA-RETOS)" and "Assessing Individual and Team Entrepreneurial Potential"; and University of Girona grants MPCUdG2016/069 and MPCUdG2016/098

The aim of this article is to describe a method for relating two compositions which combines compositional data analysis and canonical correlation analysis (CCA), and to examine its main statistical properties. We use additive log-ratio (alr) transformation on both compositions and apply standard CCA to the transformed data. We show that canonical variates are themselves log-ratios and log-contrasts. The first pair of canonical variates can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition. The second pair can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition, under the restriction that they are uncorrelated with the first pair, and so on. Using properties from changes of basis, we prove that both canonical correlations and canonical variates are invariant to the choice of divisors in alr transformation. We show how to implement the analysis and interpret the results by means of an illustration from the social sciences field using data from Kolb's Learning Style Inventory and Boyatzis' Philosophical Orientation Questionnaire, which distribute a fixed total score among several learning modes and philosophical orientations ; The authors would like to acknowledge the support provided by Spanish Health Ministry Grant CB06/02/1002 funding the research group "Epidemiology and Public Health (CIBERESP)"; Catalan Autonomous Government Consolidated Research Group Grants 2014SGR551 and 2014SGR582 funding the research groups "Compositional and Spatial Data Analysis (COSDA)" and "Leadership Development Research Centre (GLEAD)"; Spanish Economy and Competitiveness Ministry grants MINECO/FEDER-EU MTM2015-65016-C2-1-R and EDU2015-68610-R funding the projects "Compositional Data Analysis and RElated meThOdS (CODA-RETOS)" and "Assessing Individual and Team Entrepreneurial Potential"; and University of Girona grants MPCUdG2016/069 and MPCUdG2016/098

The aim of this article is to describe a method for relating two compositions which combines compositional data analysis and canonical correlation analysis (CCA), and to examine its main statistical properties. We use additive log-ratio (alr) transformation on both compositions and apply standard CCA to the transformed data. We show that canonical variates are themselves log-ratios and log-contrasts. The first pair of canonical variates can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition. The second pair can be interpreted as the log-contrast of a composition that has the maximum correlation with a log-contrast of the other composition, under the restriction that they are uncorrelated with the first pair, and so on. Using properties from changes of basis, we prove that both canonical correlations and canonical variates are invariant to the choice of divisors in alr transformation. We show how to implement the analysis and interpret the results by means of an illustration from the social sciences field using data from Kolb's Learning Style Inventory and Boyatzis' Philosophical Orientation Questionnaire, which distribute a fixed total score among several learning modes and philosophical orientations ; The authors would like to acknowledge the support provided by Spanish Health Ministry Grant CB06/02/1002 funding the research group "Epidemiology and Public Health (CIBERESP)"; Catalan Autonomous Government Consolidated Research Group Grants 2014SGR551 and 2014SGR582 funding the research groups "Compositional and Spatial Data Analysis (COSDA)" and "Leadership Development Research Centre (GLEAD)"; Spanish Economy and Competitiveness Ministry grants MINECO/FEDER-EU MTM2015-65016-C2-1-R and EDU2015-68610-R funding the projects "Compositional Data Analysis and RElated meThOdS (CODA-RETOS)" and "Assessing Individual and Team Entrepreneurial Potential"; and University of Girona grants MPCUdG2016/069 and MPCUdG2016/098