Validation of the Flexibility of Responses to Self-Critical Thoughts Scale (FoReST) in a clinical population

Background: The Flexibility of Responses to Self-Critical Thoughts Scale (FoReST) is a questionnaire that was developed to assess whether people can be psychologically flexible when experiencing critical thoughts about themselves. This measure could have important application for evaluating third wave therapies such as Acceptance and Commitment Therapy (ACT) and Compassion Focused therapy (CFT). This study investigated the validity (concurrent, predictive and incremental), internal consistency and factor structure of the FoReST in a sample of people experiencing mental health difficulties. Method: A total of 132 individuals attending Primary Care and Community Mental Health Teams within NHS Greater Glasgow and Clyde (NHS GGC) and Psychological Therapy Teams within NHS Lanarkshire participated in this study. Participants completed a battery of assessments that included the FoReST and related measures of similar constructs (psychological flexibility, self-compassion and self-criticism) and measures of mental health and well-being. A cross-sectional correlational design was used. Results: An Exploratory factor analysis described an interpretable 2-factor structure within the items of the FoReST: unworkable action and experiential avoidance. The FoReST demonstrated good internal consistency ( = .89). Concurrent validity was supported through moderate to strong correlations with similar measures and moderate correlations with other mental health and well-being outcomes. Conclusions: The FoReST appears to be a valid assessment measure for using with individuals experiencing mental health difficulties. This new measure will be of use for practitioners using ACT, CFT and those integrating both, to help monitor the process of change in flexibility and self-critical thinking across therapy. Further longitudinal studies are required to assess the test-retest reliability of the FoReST.

Probabilistic verification of satellite systems for mission critical applications

In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.