ABSTRACT
Introduction: The use of mobile devices on hospital wards to record patient vital signs and Early Warning Scores provides opportunity for secondary analysis of the data collected. This research investigated how such analysis can contribute to the understanding of the complexities of managing clinical care in hospital environments. Methods: The influence of ward type and the distribution of patient observation intervals was evaluated in relation to the timing of vital signs observation patterns in data collected from eight adult in-patient wards over a 12-month period. Actual and projected observation times were compared across patients with higher and lower National Early Warning Scores (NEWS). Results: Both ward type and the distribution of patient observation intervals were significant predictors of temporal observation patterns. Observation patterns showed evidence of grouping of observation recordings. This was, however, not found for observations of patients with higher NEWS scores (3 or more). Conclusions: Secondary analysis of vital signs observation data can reveal insights into how ward operate. The patterns of observation recordings within a ward are a reflection of ward type and the distribution of patient observation intervals. The grouping of observation recordings of patients with low NEWS (<3) result in late or early observations to fit activity peaks characteristic of the ward culture.
ABSTRACT
An amendment to this paper has been published and can be accessed via the original article.
ABSTRACT
We introduce a new approach to monitoring the activity of smartphone users based on their physical interactions with the interface. Typical events are taps, scrolling and typing, carried out to interact with apps. As compared to other measures, this directly encapsulates potential problematic physical smartphone behaviour as a signal. The approach contrasts against conventions such as self-reporting or timing activity sessions, and it focusses on active rather than passive smartphone activity. Using this alternative method, we collected all user interface interaction events from a sample of 64 participants over a period of 8 weeks, using a bespoke monitoring app called Tymer. User Smartphone Addiction was seen to significantly correlate with high levels of interaction with Lifestyle apps, particularly for female users. Interactions with Social apps in general were also associated with Smartphone Addiction. In particular, user interactions with Snapchat correlated with Smartphone Addiction, represented across all types of interface interaction. This is significant given the widespread usage of Snapchat by teenagers, and we hypothesise that the app's design provides a particularly strong pathway in support of Smartphone Addiction.
ABSTRACT
OBJECTIVE: Recent years have seen an increasing number of studies using smartphones to sample participants' mood states. Moods are usually collected by asking participants for their current mood or for a recollection of their mood states over a specific period of time. The current study investigates the reasons to favour collecting mood through current or daily mood surveys and outlines design recommendations for mood sampling using smartphones based on these findings. These recommendations are also relevant to more general smartphone sampling procedures. RESULTS: N=64 participants completed a series of surveys at the beginning and end of the study providing information such as gender, personality, or smartphone addiction score. Through a smartphone application, they reported their current mood 3 times and daily mood once per day for 8 weeks. We found that none of the examined intrinsic individual qualities had an effect on matches of current and daily mood reports. However timing played a significant role: the last followed by the first reported current mood of the day were more likely to match the daily mood. Current mood surveys should be preferred for a higher sampling accuracy, while daily mood surveys are more suitable if compliance is more important.
