Return to work among employees with mental health problems: Development and validation of a self-efficacy questionnaire

Abstract

Because of the costs to both the organization and the individual, it is important that employees who are sick-listed with mental health problems are facilitated in their return to work (RTW). In order to provide adequate interventions, it is necessary to obtain a better understanding of the RTW process of people with mental health problems. Work-related self-efficacy (SE) might play a key role within this process. This paper describes the development and validation of the return-to-work self-efficacy’ scale (RTW-SE) for employees with mental health problems. Three Dutch samples of sick-listed employees were used to validate the 11-item instrument (N=2214). Based on the factor structure and reliability results, RTW-SE was conceptualized as a unitary construct. The associations with general SE, locus of control, coping, physical workload and mental health problems support the construct validity of this scale. Most importantly, RTW-SE proved to be a robust predictor of actual return to work within three months. The encouraging preliminary psychometric properties of the scale make it a potentially valuable tool in research and in clinical practice and occupational health care settings, both before and after employees have returned to work.     

Correlates of wellbeing among African American lesbians

Although there is a growing body of knowledge about health among African American women in general, there is a dearth of information on African American lesbians. The primary purpose of this study was to investigate the correlates of health-related quality of life among African American lesbians using a cross-sectional anonymous survey with topics and measures developed by members of the African American lesbian community. Surveys were completed by 123 English speaking adult women who identified as African American lesbians and were attending the Zuna Institute's National Black Lesbian Conference. Overall, we found a very high health-related quality of life, in spite of a high frequency of health impairments. The average body mass index (BMI) for this sample was 32.2 (SD?=?8.0); 13% were morbidly obese, having a BMI of 40 or more and only 15% of the women were in a healthy weight range; advancing age was associated with poorer physical functioning, decreased physical role functioning, and more pain. Health-related quality of life was associated with depression and spirituality, but not religion. This study highlights the need for subjective measures of health-related quality of life as well as checklists of diseases and disorders.     

Confidence Intervals for the Median of a Finite Population Based on the Sign Test

This article presents methods for constructing confidence intervals for the median of a finite population under simple random sampling without replacement, stratified random sampling, and cluster sampling. The confidence intervals, as well as point estimates and test statistics, are derived from sign estimating functions which are based on the well-known sign test. Therefore, a unified approach for inference about the median of a finite population is given.     

Metamodeling of aircraft infrared signature dispersion

Existing computer simulations of aircraft InfraRed Signature (IRS) do not account for the dispersion induced by uncertainty on input data such as aircraft aspect angles and meteorological conditions. As a result, they are of little use to estimate the detection performance of optronic systems: in that case, the scenario encompasses a lot of possible situations that must indeed be addressed, but cannot be singly simulated. In this paper, a three-step methodological approach for predicting simulated IRS dispersion of imperfectly known aircraft is proposed. The first step is a sensitivity analysis. The second step consists in a Quasi-Monte Carlo survey of the code output dispersion. In the last step, a neural network metamodel of the IRS simulation code is constructed. It will allow carrying out thorough computationally demanding tasks, such as those required for optimization of an optronic sensor. This method is illustrated in a typical scenario, namely an air-to-ground full-frontal attack by a generic combat aircraft, and gives satisfactory estimation of the infrared signature dispersion.     

A computational understanding of partial and part determination coefficients

A computational understanding of partial and part determination coefficients brings additional insight concerning their interpretations in regression. It also enables one to easily identify synergistic combinations. Benefits from the practical interpretation of synergism have yet to be fully explored and exploited. Hence, this study provides a new dimension in the analysis of data.