Evaluation of an internet based weight loss intervention

PhD ThesisIntroduction: The increasing obesity epidemic requires investigation of the effectiveness, cost-effectiveness and scalability of alternative delivery methods for weight loss interventions, such as via the internet. Aims/objectives: To examine characteristics, feedback format, engagement levels, behaviour change techniques used and effectiveness of individualised feedback within internet based weight loss interventions to refine a pre-existing private sector web-based platform ‘My dietitian online’. To pilot test this refined platform, to investigate its feasibility and acceptability of this refined platform for delivery in primary care and to inform the design and conduct of a future definitive RCT. To describe website use and explore health professionals’ and participants’ views and perceptions of the intervention in terms of acceptability, feasibility and usability. Methods: (i) Systematic review of the components and effectiveness of individualised feedback within internet based weight loss interventions. (ii) A 12-month rehearsal pilot randomised controlled trial (RCT) of an internet based dietary and physical activity intervention in two population groups, with collection of data on anthropometric measures, diet, physical activity, quality of life and predictors of behaviour change. The main focus of the trial was on feasibility, including recruitment and retention rates. (iii) A mixed-methods qualitative process evaluation conducted alongside the pilot RCT comprising analysis of website usage and semi-structured interviews with participants and healthcare professionals to explore their experience of the intervention. Results The systematic review identified 14 studies. Interventions with individualised feedback led to more weight loss than those with no feedback. Studies examining different modalities of weight loss intervention were very limited. In the pilot trial 61 men with diabetes and 16 post-partum women were recruited. At 12 months retention rates for men were 61% in the intervention arm, 53% in the control arm, and for women were 53% in the intervention arm and 54% in the control arm. Website usage varied greatly between intervention participants, with 49% and 57% of men and women ii respectively ever using the website. The semi-structured interviews revealed that participants and health professionals saw an internet based intervention as an appropriate method to implement within the NHS for weight loss, with the suggestions made for integration with current services. Conclusion High attrition rates along with low adherence to the intervention were identified. Possible refinements to the website were suggested to reduce the burden and time requirements for users.County Durham and Darlington NHS Foundation Trust & Fuse via ESR

30th European Congress on Obesity (ECO 2023)

This is the abstract book of 30th European Congress on Obesity (ECO 2023

Measuring physical activity in obese populations using accelerometry

The thesis is concerned with objectively measuring human physical activity through accelerometry, and compares the effectiveness of algorithms between obese and non-obese groups. The thesis comprises three studies:Classification of Aerobic and Gym-based Exercises from Accelerometer Output. This study investigated whether accurate classification could be achieved from hip- or ankle-mounted accelerometers for a programme of aerobic exercises and free-living activities. It also examined whether accuracy was affected by obesity, and whether a single classifier could be applied across BMI groups. The study achieved high classification accuracies (85% for hip and 94% for ankle) for both obese and normal BMI groups using the same approach across groups.Walking Speed Estimation Using Accelerometry. This study aimed to develop a speed estimation model that was applicable across BMI groups, and which utilised a hip-mounted accelerometer. To achieve this, multiple accelerometer signal features were evaluated for use in a linear speed estimation model, and performance was compared between obese and normal BMI groups. The speed estimation algorithm achieved overall RMSE of 0.08ms-1for a mixed BMI group, which is comparable with previous research using homogeneous groups.Prediction of Energy Expenditure from Accelerometer Output. This study aimed to identify physiological and anthropometric parameters for use in an improved energy expenditure estimation model. Model performance was tested on a mixed BMI group. The energy expenditure prediction model incorporating subject attributes showed around 20% improvement over the standard model. This research found that current approaches to activity classification using accelerometry are equally applicable to obese groups and normal BMI groups. Walking speed prediction was shown to be possible from a hip-mounted accelerometer for both obese and normal BMI groups. Energy expenditure estimation is improved by including subject-specific parameters in the prediction model. Accelerometry is, therefore, a suitable tool for measuring different aspects of physical activity for obese and mixed BMI groups