Pre-Survey Text Messages (SMS) Improve Participation Rate in an Australian Mobile Telephone Survey: An Experimental Study

Mobile telephone numbers are increasingly being included in household surveys samples. As approach letters cannot be sent because many do not have address details, alternatives approaches have been considered. This study assesses the effectiveness of sending a short message service (SMS) to a random sample of mobile telephone numbers to increase response rates. A simple random sample of 9000 Australian mobile telephone numbers: 4500 were randomly assigned to be sent a pre-notification SMS, and the remaining 4500 did not have a SMS sent. Adults aged 18 years and over, and currently in paid employment, were eligible to participate. American Association for Public Opinion Research formulas were used to calculated response cooperation and refusal rates. Response and cooperation rate were higher for the SMS groups (12.4% and 28.6% respectively) than the group with no SMS (7.7% and 16.0%). Refusal rates were lower for the SMS group (27.3%) than the group with no SMS (35.9%). When asked, 85.8% of the pre-notification group indicated they remembered receiving a SMS about the study. Sending a pre-notification SMS is effective in improving participation in population-based surveys. Response rates were increased by 60% and cooperation rates by 79%

Reusable data visualization patterns for clinical practice

Among clinical psychologists involved in guided internet-facilitated interventions, there is an overarching need to understand patients symptom development and learn about patients need for treatment support. Data visualizations is a technique for managing enormous amounts of data and extract useful information, and is often used in developing digital tool support for decision-making. Although there exists numerous data visualisation and analytical reasoning techniques available through interactive visual interfaces, it is a challenge to develop visualizations that are relevant and suitable in a healthcare context, and can be used in clinical practice in a meaningful way. For this purpose it is necessary to identify actual needs of healthcare professionals and develop reusable data visualization components according to these needs. In this paper we present a study of decision support needs of psychologists involved in online internet-facilitated cognitive behavioural therapy. Based on these needs, we provide a library of reusable visual components using a model-based approach. The visual components are featured with mechanisms for investigating data using various levels of abstraction and causal analysis

Cloud-based management of machine learning generated knowledge for fleet data refinement

The modern mobile machinery has advanced on-board computer systems. They may execute various types of applications observing machine operation based on sensor data (such as feedback generators for more efficient operation). Measurement data utilisation requires preprocessing before use (e.g. outlier detection or dataset categorisation). As more and more data is collected from machine operation, better data preprocessing knowledge may be generated with data analyses. To enable the repeated deployment of that knowledge to machines in operation, information management must be considered; this is particularly challenging in geographically distributed fleets. This study considers both data refinement management and the refinement workflow required for data utilisation. The role of machine learning in data refinement knowledge generation is also considered. A functional cloud-managed data refinement component prototype has been implemented, and an experiment has been made with forestry data. The results indicate that the concept has considerable business potential.acceptedVersionPeer reviewe

Inaccuracies in food and physical activity diaries of obese subjects: complementary evidence from doubly labeled water and co-twin assessments

Objective:To study whether eating or physical-activity (PA) habits differ between obese and non-obese monozygotic (MZ) co-twins independent of genetic effects.Methods:Rare MZ pairs discordant for obesity (n=14, body mass index difference 5.2+/-1.8 kg m(-2)) and weight-concordant control pairs (n=10, 1.0+/-0.7 kg m(-2)), identified through a population-based registry of 24-28-year-old twins (n=658 MZ pairs), completed 3-day food and PA diaries and eating behavior questionnaires. Each twin was asked to compare his/her own eating and PA patterns with the co-twin's behavior by structured questionnaires. Accuracy of energy intake was validated by doubly labeled water.Results:Non-obese co-twins consistently reported that their obese twin siblings ate more food overall, consumed less healthy foods and exercised less than the non-obese co-twins do. However, no differences in energy intake (9.6+/-1.0 MJ per day vs 9.8+/-1.1 MJ per day, respectively) in the food diaries or in the mean PA level (1.74+/-0.02 vs 1.79+/-0.04, respectively) in the PA diaries were found between obese and non-obese co-twins. A considerable underreporting of energy intake (3.2+/-1.1 MJ per day, P=0.036) and overreporting of PA (1.8+/-0.8 MJ per day, P=0.049) was observed in the obese, but not in the non-obese co-twins.Conclusions:On the basis of rare MZ twin pairs discordant for obesity, the co-twin assessments confirmed substantial differences in eating and PA behavior between obese and non-obese persons. These may be overlooked in population studies using food and PA diaries because of considerable misreporting by the obese.International Journal of Obesity advance online publication, 15 December 2009; doi:10.1038/ijo.2009.251