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.

Estimation of whole body muscle, adipose/fat mass, validation in health and during weight loss. Development of prediction equations using MRI as reference method

Background: Body composition is affected by diseases, and affects responses to medical treatments, dosage of medicines, etc., while an abnormal body composition contributes to the causation of many chronic diseases. While we have reliable biochemical tests for certain nutritional parameters of body composition, such as iron or iodine status, and we have harnessed nuclear physics to estimate the body’s content of trace elements, the very basic quantification of body fat content and muscle mass remains highly problematic. Both body fat and muscle mass are vitally important, as they have opposing influences on chronic disease, but they have seldom been estimated as part of population health surveillance. Instead, most national surveys have merely reported BMI and waist, or sometimes the waist/hip ratio; these indices are convenient but do not have any specific biological meaning. Anthropometry offers a practical and inexpensive method for muscle and fat estimation in clinical and epidemiological settings; however, its use is imperfect due to many limitations, such as a shortage of reference data, misuse of terminology, unclear assumptions, and the absence of properly validated anthropometric equations. To date, anthropometric methods are not sensitive enough to detect muscle and fat loss. Aims: The aim of this thesis is to estimate Adipose/fat and muscle mass in health disease and during weight loss through; 1. evaluating and critiquing the literature, to identify the best-published prediction equations for adipose/fat and muscle mass estimation; 2. to derive and validate adipose tissue and muscle mass prediction equations; and 3.to evaluate the prediction equations along with anthropometric indices and the best equations retrieved from the literature in health, metabolic illness and during weight loss. Methods: a Systematic review using Cochrane Review method was used for reviewing muscle mass estimation papers that used MRI as the reference method. Fat mass estimation papers were critically reviewed. Mixed ethnic, age and body mass data that underwent whole body magnetic resonance imaging to quantify adipose tissue and muscle mass (dependent variable) and anthropometry (independent variable) were used in the derivation/validation analysis. Multiple regression and Bland-Altman plot were applied to evaluate the prediction equations. To determine how well the equations identify metabolic illness, English and Scottish health surveys were studied. Statistical analysis using multiple regression and binary logistic regression were applied to assess model fit and associations. Also, populations were divided into quintiles and relative risk was analysed. Finally, the prediction equations were evaluated by applying them to a pilot study of 10 subjects who underwent whole-body MRI, anthropometric measurements and muscle strength before and after weight loss to determine how well the equations identify adipose/fat mass and muscle mass change. Results: The estimation of fat mass has serious problems. Despite advances in technology and science, prediction equations for the estimation of fat mass depend on limited historical reference data and remain dependent upon assumptions that have not yet been properly validated for different population groups. Muscle mass does not have the same conceptual problems; however, its measurement is still problematic and reference data are scarce. The derivation and validation analysis in this thesis was satisfactory, compared to prediction equations in the literature they were similar or even better. Applying the prediction equations in metabolic illness and during weight loss presented an understanding on how well the equations identify metabolic illness showing significant associations with diabetes, hypertension, HbA1c and blood pressure. And moderate to high correlations with MRI-measured adipose tissue and muscle mass before and after weight loss. Conclusion: Adipose tissue mass and to an extent muscle mass can now be estimated for many purposes as population or groups means. However, these equations must not be used for assessing fatness and categorising individuals. Further exploration in different populations and health surveys would be valuable.

Congenital thoracic vertebral malformations in brachycephalic “screw-tailed” dog breeds: Validation of a human classification scheme and a method of Cobb angle measurement in the assessment of vertebral column deformity

Congenital vertebral malformations are common in brachycephalic “screw-tailed” dog breeds such as French bulldogs, English bulldogs, Boston terriers, and Pugs. Those vertebral malformations disrupt the normal vertebral column anatomy and biomechanics, potentially leading to deformity of the vertebral column and subsequent neurological dysfunction. The initial aim of this work was to study and determine whether the congenital vertebral malformations identified in those breeds could be translated in a radiographic classification scheme used in humans to give an improved classification, with clear and well-defined terminology, with the expectation that this would facilitate future study and clinical management in the veterinary field. Therefore, two observers who were blinded to the neurologic status of the dogs classified each vertebral malformation based on the human classification scheme of McMaster and were able to translate them successfully into a new classification scheme for veterinary use. The following aim was to assess the nature and the impact of vertebral column deformity engendered by those congenital vertebral malformations in the target breeds. As no gold standard exists in veterinary medicine for the calculation of the degree of deformity, it was elected to adapt the human equivalent, termed the Cobb angle, as a potential standard reference tool for use in veterinary practice. For the validation of the Cobb angle measurement method, a computerised semi-automatic technique was used and assessed by multiple independent observers. They observed not only that Kyphosis was the most common vertebral column deformity but also that patients with such deformity were found to be more likely to suffer from neurological deficits, more especially if their Cobb angle was above 35 degrees.