This approach, inspired by the philosophical phenomenology, was chosen because of its primary focus on the lifeworld: the world of lived experience. Rather than giving causal, behavioural explanations and using external theories and interpretive frameworks, the focus is on giving a description of the phenomenon as it is experienced by those who are studied (Finlay, 2011).
The aim of the reflective lifeworld approach is “to illuminate the essence of the phenomenon” under research. For Dahlberg (2006), an essence refers to a common thread through the variety of participants' experiences; the essential characteristics of the phenomenon “without which it would not be that phenomenon”.
Twenty-five people over 70 years of age, who considered their life to be ‘completed’ and no longer worth living, and who strongly wished to die while not being terminally or mentally ill, participated in an in-depth interview exploring their lived experience. Persons were recruited between April and September 2013.
Elderly people who live alone can be assisted by home monitoring systems that identify risk scenarios such as falls, fatigue symptoms or burglary. Given that these systems have to manage spatiotemporal data, human intervention is required to validate automatic alarms due to the high number of false positives and the need for context interpretation. The goal of this work was to provide tools to support human action, to identify such potential risk scenarios based on spatiotemporal data visualisation.
We propose the MTA (multiple temporal axes) model, a visual representation of temporal information of the activity of a single person at different locations. The main goal of this model is to visualize the behaviour of a person in their home, facilitating the identification of health-risk scenarios and repetitive patterns. We evaluate the model's insight capacity compared with other models using a standard evaluation protocol. We also test its practical suitability of the MTA graphical model in a commercial home monitoring system. In particular, we implemented 8VISU, a visualization tool based on MTA.
MTA proved to be more than 90% accurate in identify non-risk scenarios, independently of the length of the record visualised. When the spatial complexity was increased (e.g. number of rooms) the model provided good accuracy form up to 5 rooms. Therefore, user preferences and user performance seem to be balanced. Moreover, it also gave high sensitivity levels (over 90%) for 5–8 rooms. Fall is the most recurrent incident for elderly people. The MTA model outperformed the other models considered in identifying fall scenarios (66% of correctness) and was the second best for burglary and fatigue scenarios (36% of correctness). Our experiments also confirm the hypothesis that cyclic models are the most suitable for fatigue scenarios, the Spiral and MTA models obtaining most positive identifications.
Causes of death in patients with childhood-onset type 1 diabetes receiving dialysis in Japan: Diabetes Epidemiology Research International (DERI) Mortality Study
The leading causes of death were end-stage renal disease (ESRD) (36.3%), cardiovascular disease (CVD) (31.9%), and infections (20.3%). Among CVD, cerebral hemorrhage was the most frequent (38.9%) and showed a significant trend for an increase in the duration of dialysis (P = 0.01, the Cochran–Armitage trend test). The mortality from ESRD concentrated within 5 years of dialysis and that from CVD increased after 10 years of dialysis, while the mortality from infections peaked during 5 to 10 years from initiation of dialysis.
The leading causes of death in dialysis patients with type 1 diabetes were ESRD, CVD, and infections. As the duration of dialysis increased, however, CVD contributed more to mortality. Special attention should be paid to CVD, particularly cerebral hemorrhage, to improve the long-term prognosis of patients.