Women and Vulnerability to Depression: Some Personality and Clinical Factors.

En este trabajo se examinó el papel de las diferencias del sexo y de la personalidad en la vulnerabilidad a la depresión. Se describen las diferencias entre sexos en personalidad y en algunas variables clínicas para, posteriormente, analizar el papal de las variables que muestran diferencias estadísticamente significativas entre los sexos, como predictoras de la vulnerabilidad a la depresión. Para cumplir con este objetivo, se exploraron extensamente esas diferencias en dos grandes modelos de la personalidad y en algunas escalas clínicas. Nuestros datos se obtuvieron de un grupo de adultos (N = 112), 50% hombres y 50% mujeres (media de edad = 41.30; SD = 15.09; rango 17- 67). Se estudiaron las diferencias entre mujeres y hombres respecto al modelo de 3 factores, utilizando el Eysenck Personality Questionnaire, Form A (EPQ; Eysenck & Eysenck, 1975; versión española de TEA, 1986), y el modelo de 5 factores (NEO Personality Inventory -NEO-PI; Costa & McCrae, 1985). Se aplicaron también algunas escalas clínicas: Depression Inventory (BDI; Beck et al., 1979), Schizotypy Questionnaire (STQ; Claridge & Broks, 1984; versión española de Carrillo y Rojo, 1999), THARL scales (Dua, 1989, 1990; versión española de Dua y Carrillo, 1994), y The Adjustment Inventory (Bell, 1937; versión española: Cuestionario de adaptación para adultos, Cerdá, 1980). Tras estudiar las diferencias según el sexo respecto a estos factores, se estimó su valor de vulnerabilidad a la depresión mediante análisis de regresión lineal simple, siendo la escala BDI de Beck el criterio de depresión. Los resultados mostraron que existe un conjunto de variables que hacen a las mujeres más vulnerables a la depresión que a los hombres. Estas variables podrían explicarse a partir de un factor principal de emocionalidad negativa. Se discuten los resultados en el contexto de la teoría del conductismo psicológico de la depresión.En este trabajo se examinó el papel de las diferencias del sexo y de la personalidad en la vulnerabilidad a la depresión. Se describen las diferencias entre sexos en personalidad y en algunas variables clínicas para, posteriormente, analizar el papal de las variables que muestran diferencias estadísticamente significativas entre los sexos, como predictoras de la vulnerabilidad a la depresión. Para cumplir con este objetivo, se exploraron extensamente esas diferencias en dos grandes modelos de la personalidad y en algunas escalas clínicas. Nuestros datos se obtuvieron de un grupo de adultos (N = 112), 50% hombres y 50% mujeres (media de edad = 41.30; SD = 15.09; rango 17- 67). Se estudiaron las diferencias entre mujeres y hombres respecto al modelo de 3 factores, utilizando el Eysenck Personality Questionnaire, Form A (EPQ; Eysenck & Eysenck, 1975; versión española de TEA, 1986), y el modelo de 5 factores (NEO Personality Inventory -NEO-PI; Costa & McCrae, 1985). Se aplicaron también algunas escalas clínicas: Depression Inventory (BDI; Beck et al., 1979), Schizotypy Questionnaire (STQ; Claridge & Broks, 1984; versión española de Carrillo y Rojo, 1999), THARL scales (Dua, 1989, 1990; versión española de Dua y Carrillo, 1994), y The Adjustment Inventory (Bell, 1937; versión española: Cuestionario de adaptación para adultos, Cerdá, 1980). Tras estudiar las diferencias según el sexo respecto a estos factores, se estimó su valor de vulnerabilidad a la depresión mediante análisis de regresión lineal simple, siendo la escala BDI de Beck el criterio de depresión. Los resultados mostraron que existe un conjunto de variables que hacen a las mujeres más vulnerables a la depresión que a los hombres. Estas variables podrían explicarse a partir de un factor principal de emocionalidad negativa. Se discuten los resultados en el contexto de la teoría del conductismo psicológico de la depresión

Breaking Them In or Revealing Their Best? Reframing Socialization Around Newcomer Self-expression

Socialization theory has focused on enculturating new employees such that they develop pride in their new organization and internalize its values. Drawing on authenticity research, we propose that the initial stage of socialization leads to more effective employment relationships when it instead primarily encourages newcomers to express their personal identities. In a field experiment carried out in a large business process outsourcing company, we found that initial socialization focused on personal identity (emphasizing newcomers' authentic best selves) led to greater customer satisfaction and employee retention after six months as compared to (a) socialization that focused on organizational identity (emphasizing the pride to be gained from organizational affiliation) and (b) the organization's traditional approach, which focused primarily on skills training. To confirm causation and explore the mechanisms underlying the effects, we replicated the results in a laboratory experiment. We found that individuals working temporarily as part of a research team were more engaged and satisfied with their work, performed their tasks more effectively, and were more likely to return to work when initial socialization focused on personal identity as compared to a focus on organizational identity or a control condition. In addition, authentic self-expression mediated these relationships. We call for a new direction in socialization theory that examines how both organizations and employees benefit by emphasizing newcomers' authentic best selves

Breaking Them In or Eliciting Their Best? Reframing Socialization Around Newcomers’ Authentic Self-Expression

Socialization theory has focused on enculturating new employees such that they develop pride in their new organization and internalize its values. We draw on authenticity research to theorize that the initial stage of socialization leads to more effective employment relationships when it instead primarily encourages newcomers to express their personal identities. In a field experiment carried out in a large business process outsourcing company in India, we found that initial socialization focused on personal identity (emphasizing newcomers’ authentic best selves) led to greater customer satisfaction and employee retention after six months than socialization that focused on organizational identity (emphasizing the pride to be gained from organizational affiliation) or the organization’s traditional approach, which focused primarily on skills training. To confirm causation and explore the mechanisms underlying the effects, we replicated the results in a laboratory experiment in a U.S. university. We found that individuals working temporarily as part of a research team were more engaged and satisfied with their work, performed their tasks more effectively, and were less likely to quit when initial socialization focused on personal identity rather than on organizational identity or a control condition. In addition, authentic self-expression mediated these relationships. We call for a new direction in socialization theory that examines how both organizations and employees can benefit by emphasizing newcomers’ authentic best selves

Lean Principles, Learning, and Knowledge Work: Evidence from a Software Services Provider

In this paper, we examine the applicability of lean production to knowledge work by investigating the implementation of a lean production system at an Indian software services firm. We first discuss specific aspects of knowledge work—task uncertainty, process invisibility, and architectural ambiguity—that call into question the relevance of lean production in this setting. Then, combining a detailed case study and empirical analysis, we find that lean software projects perform better than non-lean software projects at the company for most performance outcomes. We document the influence of the lean initiative on internal processes and examine how the techniques affect learning by improving both problem identification and problem resolution. Finally, we extend the lean production framework by highlighting the need to (1) identify problems early in the process and (2) keep problems and solutions together in time, space, and person

Does Automated Unit Test Generation Really Help Software Testers? A Controlled Empirical Study

Work on automated test generation has produced several tools capable of generating test data which achieves high structural coverage over a program. In the absence of a specification, developers are expected to manually construct or verify the test oracle for each test input. Nevertheless, it is assumed that these generated tests ease the task of testing for the developer, as testing is reduced to checking the results of tests. While this assumption has persisted for decades, there has been no conclusive evidence to date confirming it. However, the limited adoption in industry indicates this assumption may not be correct, and calls into question the practical value of test generation tools. To investigate this issue, we performed two controlled experiments comparing a total of 97 subjects split between writing tests manually and writing tests with the aid of an automated unit test generation tool, EvoSuite. We found that, on one hand, tool support leads to clear improvements in commonly applied quality metrics such as code coverage (up to 300% increase). However, on the other hand, there was no measurable improvement in the number of bugs actually found by developers. Our results not only cast some doubt on how the research community evaluates test generation tools, but also point to improvements and future work necessary before automated test generation tools will be widely adopted by practitioners

Between home and work: Commuting as an opportunity for role transitions

Across the globe, every workday people commute an average of 38 minutes each way, yet surprisingly little research has examined the implications of this daily routine for work-related outcomes. Integrating theories of boundary work, self-control, and work-family conflict, we propose that the commute to work serves as a liminal role transition between home and work roles, prompting employees to engage in boundary management strategies. Across three field studies (n = 1,736), including a four-week-long intervention study, we find that lengthy morning commutes are more aversive for employees with lower trait self-control and greater work-family conflict, leading to decreased job satisfaction and increased turnover. In addition, we find that employees who engage in a specific boundary management strategy we term role-clarifying prospection (i.e., thinking about the upcoming work role) are less likely to be negatively affected by lengthy commutes to work. Results further show that employees with higher levels of trait self-control are more likely to engage in role-clarifying prospection, and employees who experience higher levels of work-family conflict are more likely to benefit from role-clarifying prospection. Although the commute to work is typically seen as an undesirable part of the workday, our theory and results point to the benefits of using it as an opportunity to transition into one’s work role

Constructing Search Spaces for Search-Based Software Testing Using Neural Networks

A central requirement for any Search-Based Software Testing (SBST) technique is a convenient and meaningful fitness landscape. Whether one follows a targeted or a diversification driven strategy, a search landscape needs to be large, continuous, easy to construct and representative of the underlying property of interest. Constructing such a landscape is not a trivial task often requiring a significant manual effort by an expert. We present an approach for constructing meaningful and convenient fitness landscapes using neural networks (NN) – for targeted and diversification strategies alike. We suggest that output of an NN predictor can be interpreted as a fitness for a targeted strategy. The NN is trained on a corpus of execution traces and various properties of interest, prior to searching. During search, the trained NN is queried to predict an estimate of a property given an execution trace. The outputs of the NN form a convenient search space which is strongly representative of a number of properties. We believe that such a search space can be readily used for driving a search towards specific properties of interest. For a diversification strategy, we propose the use of an autoencoder; a mechanism for compacting data into an n-dimensional “latent” space. In it, datapoints are arranged according to the similarity of their salient features. We show that a latent space of execution traces possesses characteristics of a convenient search landscape: it is continuous, large and crucially, it defines a notion of similarity to arbitrary observations