A Social Practice Theory Perspective to Exploring the Lived Experiences of Physical Activity in People with Type-2 Diabetes in Urban Nigeria

This thesis aims to gain a greater understanding of the social, material and historical processes underlying physical activity participation in the lived experiences of people with type-2 diabetes in Urban Nigeria. Using social practice theory and life-course perspective as guiding theoretical frameworks, a qualitative narrative inquiry was conducted with thirty-five people with type-2 diabetes receiving outpatient care at the University College Hospital Ibadan, Oyo state, Nigeria. Through a multi-modal research design, data were collected in three phases: Firstly, a narrative interview study was conducted to obtain biographical accounts of how people’s relationship with physical activity has evolved over their life course. Secondly, participants took part in a one-week activity tracking and diary study to capture their daily life patterns of activity. Thirdly, the diary study was followed up with a visual elicitation interview co-explore their captured data to gain deeper access to the context of their daily lives and how physical activity fits within this context. Additionally, an informal contextual inquiry involving observations and discussions with healthcare professionals was conducted to help build a bigger picture of the context in which people lived. Four separate analyses of the research data were performed. The first involved a case-based narrative analysis of six of the thirty-five participants’ data to understand the nuances and peculiarities of their individual lived experiences. This was followed by a cluster analysis of participants’ daily activities to identify groups of participants with similar patterns of activities. The third included a thematic analysis of participants’ experiences of physical activity over the life course. Lastly, a separate thematic analysis was conducted to understand participants’ knowledge about physical activity as part of their type-2 diabetes management. The cluster analysis of people with type-2 diabetes’ daily activities identified six participant sub-groups, with members of each group having similar patterns of activities. Physical activity patterns also varied across the life course and were strongly implicated in processes including changing social roles within the family life trajectory, transitions to retirement, ageing, type-2 diabetes diagnosis, gender norms, absence of an exercise culture, and negative age stereotypes. The research makes three contributions. Firstly, it makes an empirical contribution by providing an in-depth multi-layered account of the socio-historical dynamics of physical activity in the lived experiences of people with type-2 diabetes in an urban Nigerian context. Secondly, the research offers a methodological contribution by demonstrating how combining SPT with concepts from life-course perspectives can facilitate a relational and temporal approach to exploring the lived experiences of physical activity in people with Type-2 diabetes in Urban Nigeria. Thirdly, the research findings contribute to the growing theoretical debates that physical activity engagement is not a static or linear behaviour but a dynamic, ongoing process of change that encompasses an interplay of transitions, turning points, and social interactions in people’s lives

Integrating art into bodily interactions : exploring digital art in HCI design to foster somaesthetic experiences

PhD ThesisMy interdisciplinary doctoral research of this thesis explored how interaction design – with a combination of digital art, body-centred practice and biophysical sensing technology – cultivates self-awareness and self-reflection to foster somaesthetic experiences in everyday walking. My research followed a Research through Design (RtD) approach to provide design artefacts as examples of research in the expanded territory of Somaesthetic Design, technology-enhanced body-centred practices and digital art applied in interaction design. Background research included a critical review of Affective Computing, the concept of somaesthetic experience, existing body-centred practices (e.g. mindfulness and deep listening), HCI designs for somaesthetic experiences, and interactive digital art applications (using biophysical data as input) to express bodily activities. In methodological terms the research could be summarized as a process of ‘making design theories’ (Redström, 2017) that draws upon a Research through Design (RtD) approach. The whole research process could be described with a ‘bucket’ model in making design theories (Redström, 2017): identified initial design space as the initial ‘bucket’; derived the first design artefact ‘Ambient Walk’ as a ‘fact’ to represent the initial design space and the cause of transitioning, re-accenting process from mindfulness to ‘adding a sixth-sense’ (i.e. to extend the initial ‘bucket’); the making of second design artefact ‘Hearing the Hidden’ as a ‘fact’ to represent the re-accented research rationale in designing for somaesthetic experience by ‘adding a sixth sense’. I followed a qualitative approach to evaluate individual user feedbacks on enhancing somaesthetic experiences, the aspects to be considered in designing for experiences, and how my design process contributed to refining design for experiences. At the end of this thesis, I discuss the findings from the two practical projects regarding the somaesthetic experiences that have been provoked during users’ engagement with ‘Ambient Walk’ and ‘Hearing the Hidden’; the inclusion of bodily interactions with surroundings in somaesthetic design; the use of ‘provotypes’ in experience-centred design practices; and the benefit of integrating digital art into technology for body-centred practices

The Utility of a Protection Motivation Theory Framework for Understanding Sedentary Behaviour

This study aimed to 1) examine the factor structure and composition of sedentary-derived Protection Motivation Theory (PMT) constructs and 2) determine the utility of these constructs in predicting general and leisure sedentary goal intention (GI), implementation intention (II), and sedentary behaviour (SB). PMT, GI, II constructs, and a modified SB questionnaire were completed by undergraduate students. After completing socio-demographics and the PMT items (n = 787), participants were randomized to complete general or leisure intention and SB items. Irrespective of model, principal axis factor analysis revealed that the PMT items grouped into eight coherent and interpretable factors. Using linear regression, general and leisure models predicted 5% and 6% of the variance in GI, 12% and 18% of the variance in II, and 6% and 7% of the variance in SB, respectively. Support now exists for the tenability of an eight-factor PMT sedentary model with modest predictability for intentions and behaviour

Yoga for HEART (Health Empowerment and Realizing Transformation) Intervention to Enhance Motivation for Physical Activity in Older Adults

abstract: Cardiovascular disease (CVD) is the leading cause of mortality in the U.S. While physical activity can reduce CVD risk, most adults do not engage in adequate physical activity to maintain or improve health. Older adults are less likely to participate in physical activity and experience a greater burden of CVD compared to younger adults. Despite knowledge of motivators and barriers to physical activity, the challenge to reduce cardiovascular risk in the older adult population remains unmet. Older adults face unique and complex barriers to physical activity, including limited social contextual resources and behavioral change processes. Interventions to enhance wellness motivation have demonstrated potential in promoting health behavior change among older adults. The purpose of this study was to examine the feasibility of the Yoga for HEART (Health Empowerment and Realizing Transformation) Intervention to increase motivation for physical activity and improve cardiovascular health in older adults. A pilot randomized controlled trial design was used. The Intervention group received Yoga for HEART, a 12-week program to foster motivation for health behavior change. The Control group received a 12-week group yoga program that did not contain theory-based components. The intervention was based on Wellness Motivation Theory, conceptualizing health behavior change as dynamic process of intention formation and goal-directed behavior leading to the development of new and positive health patterns. Critical inputs (i.e., empowering education, motivational support, social network support) were designed to promote social contextual resources and behavioral change processes to increase motivation for physical activity and improve cardiovascular health. Specific Aims were to: (a) examine intervention acceptability, demand, and fidelity, and (b) evaluate intervention efficacy in promoting physical activity and improving cardiovascular health through increased social contextual resources and behavioral change processes. Participants in the Intervention group realized a significant reduction in body mass index (BMI) from baseline to 12 weeks when compared to participants in the Control group. Intervention group participants demonstrated improvement in theoretical mechanisms (i.e., self-knowledge, motivation appraisal, self-regulation, environmental resources) and intended outcomes (i.e., body composition) when compared to Control group participants. Findings from this study support the feasibility of the Yoga for HEART Intervention in older adults.Dissertation/ThesisDoctoral Dissertation Nursing and Healthcare Innovation 201

Venice From Above: Preserving Venetian Bell Towers

This project aids in the preservation of Venetian bells and towers by improving upon the Venice Project Center’s database, achieved through detailed quantitative surveys of bell towers and creation of interactive virtual tours. To provide a more comprehensive presentation of bell tower data, the Bells Web App was redesigned with improved functionality and visuals. The project explored new promotional methods to increase traffic to the Bells App to increase awareness of the state of the bells and towers. This project also investigated ways to measure the effects of bell swinging forces to determine their impact on the structural integrity of a tower. Finally, the project assessed the safety and accessibility of bell towers to determine if they can be opened to visitation in the future

Social-Context Middleware for At-Risk Veterans

Many veterans undergo challenges when reintegrating into civilian society. These challenges include readapting to their communities and families. During the reintegration process veterans have difficulties finding employment, education or resources that aid veteran health. Research suggests that these challenges often result in veterans encountering serious mental illness. Post-Traumatic Stress Disorder (PTSD) is a common mental disease that veterans often develop. This disease impacts between 15-20% of veterans. PTSD increases the likelihood of veterans engaging in high risk behaviors which may consist of impulsivity, substance abuse, and angry outbursts. These behaviors raise the veterans’ risk of becoming violent and lashing out at others around them. In more recent studies the VA has started to define PTSD by its association to specific high risk behaviors rather than defining PTSD based on a combination of psychiatric symptoms. Some researchers have suggested that high risk behaviors -- extreme anger (i.e., rage or angry outbursts) is particularly problematic within the context of military PTSD. Comparatively little research has been done linking sensor based systems to identify these angry episodes in the daily lives of military veterans or others with similar issues. This thesis presents a middleware solution for systems that work to detect, and with additional work possibly prevent, angry outbursts (also described in psychological literature as “rage”) using physiological sensor data and context-aware technology. This paper will cover a range of topics from methods for collecting system requirements for a subject group to the development of a social-context aware middleware. In doing such, the goal is to present a system that can be constructed and used in an in lab environment to further the research of building real-world systems that predict crisis events, setting the state for early intervention methods based on this approach

A spherical representation of sensors and a model based approach for classification of human activities

Physical inactivity is a leading risk factor in public health and inactive people are more vulnerable to having non-communicable diseases (NCDs), for example, autoimmune diseases, strokes, most heart diseases, diabetes, chronic kidney disease, and others. In addition, levels of physical activity may be an indicator of health problems in older adult individuals, a particular problem in many societies where there is a growing ratio of old adults age 65 and over. Identifying levels of physical activity may have a significant effect on fitness and reducing healthcare costs in the future. Thus, finding approaches for measuring the individuals’ activities is an important need, in order to provide information about their quality of life and to examine their current health status. This thesis explores the possibility of using low-cost wearable accelerometer based inertial sensors to determine activities during daily living. Two data sources were used for this investigation. The first was a locally collected data set recorded from individuals with Parkinson’s disease in their own homes where they were asked to stand up from their favourite chair and then do different daily activities (Bridge data set). The second was a data set collected in a movement laboratory of the Fredrich-Alexander university and measures 19 participants doing daily activities (sit, stand, washing dishes, sweeping, walking, etc) in controlled conditions (Benchmark data set). Both studies used accelerometer based measurements as these are widely used in wearable and portable technologies such as smartphones, and are now finding use in health care applications. Two areas of research are considered. In the first, accelerometer data were considered in relation to the surface of a sphere of radius 1g (i.e. magnitude of the acceleration due to earth gravitate). This research looked at sensor placement, window size and novel features based on the ‘gravity sphere’. Decision Trees and Na¨ıve Bayes classifiers were used as a baseline classifier on both data sets and k-Nearest Neighbour was used on the Bench Mark data set only. The classification results of a small set of activities of a single individual from first data set show that Na¨ıve Bayes (NB) had a better overall accuracy rate than Decision Trees (DTs), where the results are 85.41% and 78.56% for both NB and DTs respectively. The second area of work considered the possibility of using models of the dynamic system of the human movement as the basis for movement classification. Data from the accelerometers were used to evaluate two approaches that exploited the modelling capacity of a system identification algorithm. The two methods, which are called Prediction Measuring (PM) and Model Matching (MM), used the recursive least square method to identify a model for each class (activity). The Benchmark data set was used to verify the proposed methods. PM method achieved better classification accuracy comparing to MM method, with 71% and 59% respectively