Return-to-Work Self-Efficacy:Development and Validation of a Scale in Claimants with Musculoskeletal Disorders

Introduction We report on the development and validation of a 10-item scale assessing self-efficacy within the return-to-work context, the Return-to-Work Self-Efficacy (RTWSE) scale. Methods Lost-time claimants completed a telephone survey 1 month (n = 632) and 6 months (n = 446) after a work-related musculoskeletal injury. Exploratory (Varimax and Promax rotation) and confirmatory factor analyses of self-efficacy items were conducted with two separate subsamples at both time points. Construct validity was examined by comparing scale measurements and theoretically derived constructs, and the phase specificity of RTWSE was studied by examining changes in strength of relationships between the RTWSE Subscales and the other constructs at both time measures. Results Factor analyses supported three underlying factors: (1) Obtaining help from supervisor, (2) Coping with pain (3) Obtaining help from co-workers. Internal consistency (alpha) for the three subscales ranged from 0.66 to 0.93. The total variance explained was 68% at 1-month follow-up and 76% at 6-month follow-up. Confirmatory factor analyses had satisfactory fit indices to confirm the initial model. With regard to construct validity: relationships of RTWSE with depressive symptoms, fear-avoidance, pain, and general health, were generally in the hypothesized direction. However, the hypothesis that less advanced stages of change on the Readiness for RTW scale would be associated with lower RTWSE could not be completely confirmed: on all RTWSE subscales, RTWSE decreased significantly for a subset of participants who started working again. Moreover, only Pain RTWSE was significantly associated with RTW status and duration of work disability. With regard to the phase specificity, the strength of association between RTWSE and other constructs was stronger at 6 months post-injury compared to 1 month post-injury. Conclusions A final 10-item version of the RTWSE has adequate internal consistency and validity to assess the confidence of injured workers to obtain help from supervisor and co-workers and to cope with pain. With regard to phase specificity, stronger associations between RTWSE and other constructs at 6-month follow-up suggest that the association between these psychological constructs consolidates over time after the disruptive event of the injury

Combining Experiments and Simulations Using the Maximum Entropy Principle

A key component of computational biology is to compare the results of computer modelling with experimental measurements. Despite substantial progress in the models and algorithms used in many areas of computational biology, such comparisons sometimes reveal that the computations are not in quantitative agreement with experimental data. The principle of maximum entropy is a general procedure for constructing probability distributions in the light of new data, making it a natural tool in cases when an initial model provides results that are at odds with experiments. The number of maximum entropy applications in our field has grown steadily in recent years, in areas as diverse as sequence analysis, structural modelling, and neurobiology. In this Perspectives article, we give a broad introduction to the method, in an attempt to encourage its further adoption. The general procedure is explained in the context of a simple example, after which we proceed with a real-world application in the field of molecular simulations, where the maximum entropy procedure has recently provided new insight. Given the limited accuracy of force fields, macromolecular simulations sometimes produce results that are at not in complete and quantitative accordance with experiments. A common solution to this problem is to explicitly ensure agreement between the two by perturbing the potential energy function towards the experimental data. So far, a general consensus for how such perturbations should be implemented has been lacking. Three very recent papers have explored this problem using the maximum entropy approach, providing both new theoretical and practical insights to the problem. We highlight each of these contributions in turn and conclude with a discussion on remaining challenges