Exploring the data divide through a social practice lens: A qualitative study of UK cattle farmers.

Appropriate management decisions are key for sustainable and profitable beef and dairy farming. Data-driven technologies aim to provide information which can improve farmers' decision-making practices. However, data-driven technologies have resulted in the emergence of a "data divide", in which there is a gap between the generation and use of data. Our study aims to further understand the data divide by drawing on social practice theory to recognise the emergence, linkages, and reproduction of youngstock data practices on cattle farms in the UK. Eight focus groups with fifteen beef and nineteen dairy farmers were completed. The topics of discussion included data use, technology use, disease management in youngstock, and future goals for their farm. The transcribed data were analysed using reflexive thematic analysis with a social practice lens. Social practice theory uses practices as the unit of analysis, rather than focusing on individual behaviours. Practices are formed of three elements: meaning (e.g., beliefs), materials (e.g., objects), and competencies (e.g., skills) and are connected in time and space. We conceptualised the data divide as a disconnection of data collection practices and data use and interpretation practices. Consequently, we were able to generate five themes that represent these breaks in connection.Our findings suggest that a data divide exists because of meanings that de-stabilise practices, tensions in farmers' competencies to perform practices, spatial and temporal disconnects, and lack of forms of feedback on data practices. The data preparation practice, where farmers had to merge different data sources or type up handwritten data, had negative meanings attached to it and was therefore sometimes not performed. Farmers tended to associate data and technology practices with larger dairy farms, which could restrict beef and small-scale dairy farms from performing these practices. Some farmers suggested that they lacked the skills to use technologies and struggled to transform their data into meaningful outputs. Data preparation and data use and interpretation practices were often tied to an office space because of the required infrastructure, but farmers preferred to spend time outdoors and with their animals. There appeared to be no normalisation of what data should be collected or what data should be analysed, which made it difficult for farmers to benchmark their progress. Some farmers did not have access to discussion groups or veterinarians who were interested in data and therefore could not get feedback on their data practices.These results suggest that the data divide exists because of three types of disconnect: a disconnect between elements within a practice because of tensions in competencies or negative meanings to perform a practice; a disconnect between practices because of temporal or spatial differences; and a break in the reproduction of practices because of lack of feedback on their practices. Data use on farms can be improved through transformation of practices by ensuring farmers have input in the design of technologies so that they align with their values and competencies.

QTc interval and resting heart rate as long-term predictors of mortality in type 1 and type 2 diabetes mellitus: a 23-year follow-up.

AIMS/HYPOTHESIS: We evaluated the association of QT interval corrected for heart rate (QT(c)) and resting heart rate (rHR) with mortality (all-causes, cardiovascular, cardiac, and ischaemic heart disease) in subjects with type 1 and type 2 diabetes. METHODS: We followed 523 diabetic patients (221 with type 1 diabetes, 302 with type 2 diabetes) who were recruited between 1974 and 1977 in Switzerland for the WHO Multinational Study of Vascular Disease in Diabetes. Duration of follow-up was 22.6 +/- 0.6 years. Causes of death were obtained from death certificates, hospital records, post-mortem reports, and additional information given by treating physicians. RESULTS: In subjects with type 1 diabetes QT(c), but not rHR, was associated with an increased risk of: (1) all-cause mortality (hazard ratio [HR] 1.10 per 10 ms increase in QT(c), 95% CI 1.02-1.20, p = 0.011); (2) mortality due to cardiovascular (HR 1.15, 1.02-1.31, p = 0.024); and (3) mortality due to cardiac disease (HR 1.19, 1.03-1.36, p = 0.016). Findings for subjects with type 2 diabetes were different: rHR, but not QT(c) was associated with mortality due to: (1) all causes (HR 1.31 per 10 beats per min, 95% CI 1.15-1.50, p < 0.001); (2) cardiovascular disease (HR 1.43, 1.18-1.73, p < 0.001); (3) cardiac disease (HR 1.45, 1.19-1.76, p < 0.001); and (4) ischaemic heart disease (HR 1.52, 1.21-1.90, p < 0.001). Effect modification of QT(c) by type 1 and rHR by type 2 diabetes was statistically significant (p < 0.05 for all terms of interaction). CONCLUSIONS/INTERPRETATION: QT(c) is associated with long-term mortality in subjects with type 1 diabetes, whereas rHR is related to increased mortality risk in subjects with type 2 diabetes.

Effects of alcohol consumption on mortality in patients with Type 2 diabetes mellitus.

AIMS/HYPOTHESIS: Moderate alcohol intake has been associated with increased life expectancy due to reduced mortality from cardiovascular disease. We prospectively examined the effects of alcohol consumption on mortality in Type 2 diabetic patients in Switzerland. METHODS: A total of 287 patients with Type 2 diabetes mellitus (125 women, 162 men), recruited in Switzerland for the WHO Multinational Study of Vascular Disease in Diabetes, were included in this study. After a follow-up period of 12.6+/-0.6 years (means +/- SD), mortality from CHD and from all causes was assessed. RESULTS: During the follow-up, 70 deaths occurred (21 from CHD, 49 from other causes). Compared with non-drinkers, alcohol consumers who drank alcohol 1 to 15 g, 16 to 30 g and 30 g or more per day had the following risk rates of death from CHD: 0.87 (95% CI: 0.25 to 2.51, NS), 0.00 (95% CI: 0.00 to 0.92, p less than 0.05) and 0.37 (95% CI, 0.01 to 2.42, NS), respectively. The corresponding risk rates of death from all causes were 1.27 (95% CI: 0.68 to 2.28, NS), 0.36 (95% CI: 0.09 to 0.99, p less than 0.05) and 1.66 (95% CI: 0.76 to 3.33, NS). CONCLUSIONS/INTERPRETATION: In Swiss Type 2 diabetic patients moderate alcohol consumption of 16 to 30 g per day was associated with reduced mortality from CHD and from all causes. Alcohol intake above 30 g per day was associated with a tendency towards increased all-cause mortality.