Work values as predictors of entrepreneurial career intentions: A longitudinal analysis of gender effects

Purpose - Work values are an important characteristic to understand gender differences in career intentions, but how gender affects the relationship between values and career intentions is not well established. The purpose of this paper is to investigate whether gender moderates the effects of work values on level and change of entrepreneurial intentions (EI). Design/methodology/approach - In total, 218 German university students were sampled regarding work values and with EI assessed three times over the course of 12 months. Data were analysed with latent growth modelling. Findings - Self-enhancement and openness to change values predicted higher levels and conservation values lower levels of EI. Gender moderated the effects of enhancement and conservation values on change in EI. Research limitations/implications - The authors relied on self-reported measures and the sample was restricted to university students. Future research needs to verify to what extent these results generalize to other samples and different career fields, such as science or nursing. Practical implications - The results imply that men and women are interested in an entrepreneurial career based on the same work values but that values have different effects for men and women regarding individual changes in EI. The results suggest that the prototypical work values of a career domain seem important regarding increasing the career intent for the gender that is underrepresented in that domain. Originality/value - The results enhance understanding of how gender affects the relation of work values and a specific career intention, such as entrepreneurship.

The evolution of helping and harming on graphs: the return of the inclusive fitness effect.

Evolutionary graph theory has been proposed as providing new fundamental rules for the evolution of co-operation and altruism. But how do these results relate to those of inclusive fitness theory? Here, we carry out a retrospective analysis of the models for the evolution of helping on graphs of Ohtsuki et al. [Nature (2006) 441, 502] and Ohtsuki & Nowak [Proc. R. Soc. Lond. Ser. B Biol. Sci (2006) 273, 2249]. We show that it is possible to translate evolutionary graph theory models into classical kin selection models without disturbing at all the mathematics describing the net effect of selection on helping. Model analysis further demonstrates that costly helping evolves on graphs through limited dispersal and overlapping generations. These two factors are well known to promote relatedness between interacting individuals in spatially structured populations. By allowing more than one individual to live at each node of the graph and by allowing interactions to vary with the distance between nodes, our inclusive fitness model allows us to consider a wider range of biological scenarios leading to the evolution of both helping and harming behaviours on graphs.

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-Part I

Introduction.- Knowledge of predictors of an unfavourable outcome, e.g. non-return to work after an injury enables to identify patients at risk and to target interventions for modifiable predictors. It has been recently shown that INTERMED; a tool to measure biopsychosocial complexity in four domains (biologic, psychologic, social and care, with a score between 0-60 points) can be useful in this context. The aim of this study was to set up a predictive model for non-return to work using INTERMED in patients in vocational rehabilitation after orthopaedic injury.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 consecutively included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic or sport related injury. Two years after discharge, a questionnaire regarding return to work was sent (1502 returned their questionnaires). In addition to INTERMED, 18 predictors known at baseline of the rehabilitation were selected based on previous research. A multivariable logistic regression was performed.Results.- In the multivariate model, not-returning to work at 2 years was significantly predicted by the INTERMED: odds-ratio (OR) 1.08 (95% confidence interval, CI [1.06; 1.11]) for a one point increase in scale; by qualified work-status before the injury OR = 0.74, CI (0.54; 0.99), by using French as preferred language OR = 0.60, CI (0.45; 0.80), by upper-extremity injury OR = 1.37, CI (1.03; 1.81), by higher education (> 9 years) OR = 0.74, CI (0.55; 1.00), and by a 10 year increase in age OR = 1.15, CI (1.02; 1.29). The area under the receiver-operator-characteristics curve (ROC)-curve was 0.733 for the full model (INTERMED plus 18 variables).Discussion.- These results confirm that the total score of the INTERMED is a significant predictor for return to work. The full model with 18 predictors combined with the total score of INTERMED has good predictive value. However, the number of variables (19) to measure is high for the use as screening tool in a clinic.

There and back again? Combining habitat suitability modelling and connectivity analyses to assess a potential return of the otter to Switzerland

After a steady decline in the early 20th century, several terrestrial carnivore species have recently recovered in Western Europe, either through reintroductions or natural recolonization. Because of the large space requirements of these species and potential conflicts with human activities, ensuring their recovery requires the implementation of conservation and management measures that address the environmental, landscape and social dimensions of the problem. Few examples exist of such integrated management. Taking the case of the otter (Lutra lutra) in Switzerland, we propose a multi-step approach that allows to (1) identify areas with potentially suitable habitat, (2) evaluate their connectivity, (3) verify the potentiality of the species recolonization from populations in neighbouring countries. We showed that even though suitable habitat is available for the species and the level of structural connectivity within Switzerland is satisfactory, the level of connectivity with neighbouring populations is crucial to prioritize strategies that favour the species recovery in the field. This research is the first example integrating habitat suitability and connectivity assessment at different scales with other factors in a multi-step assessment for species recovery.

Self perceptions as predictors for return to work 2 years after rehabilitation in orthopedic trauma inpatients.

Purpose This study aimed to identify self-perception variables which may predict return to work (RTW) in orthopedic trauma patients 2 years after rehabilitation. Methods A prospective cohort investigated 1,207 orthopedic trauma inpatients, hospitalised in rehabilitation, clinics at admission, discharge, and 2 years after discharge. Information on potential predictors was obtained from self administered questionnaires. Multiple logistic regression models were applied. Results In the final model, a higher likelihood of RTW was predicted by: better general health and lower pain at admission; health and pain improvements during hospitalisation; lower impact of event (IES-R) avoidance behaviour score; higher IES-R hyperarousal score, higher SF-36 mental score and low perceived severity of the injury. Conclusion RTW is not only predicted by perceived health, pain and severity of the accident at the beginning of a rehabilitation program, but also by the changes in pain and health perceptions observed during hospitalisation.

INTERMED predicts non-return to work in an occupational rehabilitation setting for individuals with orthopaedic trauma-part 2

Introduction.- The model presented in part I (19 predictors) had good predictive values for non-return to work 2 years after vocational rehabilitation for orthopaedic trauma. However, the number of predictors is high for the detection of patients at risk in a clinic. For example, the INTERMED for itself consists of 20 questions and needs 20 minutes to be filled in. For this reason, the aim of this study was to compare the predictive value of different models for the prediction of non-return to work.Patients and methods.- In this longitudinal prospective study, the cohort consisted of 2156 included inpatients with orthopaedic trauma attending a rehabilitation hospital after a work, traffic, sport or leisure related injury. Two years after discharge, 1502 patients returned a questionnaire regarding return to work. We compared the area under the receiver-operator-characteristics curve (ROC) between different models: INTERMED total score, the 4 partial INTERMED scores, the items of the most predictive partial score; with or without confounders.Results.- The ROC for the total score of the INTERMED plus the five confounders of the of the part one (qualified work, speaking French, lesion of upper extremity, education and age) was 0.72. The sole partial INTERMED score to predict return to work was the social sub score. The ROC for the five items of the latter sub score of the INTERMED was 0.69. The ROC for the five items of the social subscale of the INTERMED combined with five predictors was 0.73. This was significantly better than the use of only the five items from INTERMED alone (delta 0.034; 95% CI 0.017 to .050). The model presented in part I (INTERMED total score plus 18 predictors) was not significantly better than the five items INTERMED social score plus five confounders.Discussion.- The use of a model with ten variables (INTERMED social five items plus five confounders) has good predictive value to detect patients not returning to work after vocational rehabilitation after orthopaedic trauma. The parsimony of this model facilitates its use in a clinic for the detection of patients at risk.