Goal-setting is often used in eHealth applications for behavior change as it motivates and helps to stay focused on a desired outcome. However, for goals to be effective, they need to meet criteria... Show moreGoal-setting is often used in eHealth applications for behavior change as it motivates and helps to stay focused on a desired outcome. However, for goals to be effective, they need to meet criteria such as being specific, measurable, attainable, relevant and time-bound (SMART). Moreover, people need to be confident to reach their goal. We thus created a goal-setting dialog in which the virtual coach Jody guided people in setting SMART goals. Thereby, Jody provided personalized vicarious experiences by showing examples from other people who reached a goal to increase people's confidence. These experiences were personalized, as it is helpful to observe a relatable other succeed. Data from an online study with a between-subjects with pre-post measurement design (n=39 participants) provide credible support that personalized experiences are seen as more motivating than generic ones. Motivational factors for participants included information about the goal, path to the goal, and the person who accomplished a goal, as well as the mere fact that a goal was reached. Participants also had a positive attitude toward Jody. We see these results as an indication that people are positive toward using a goal-setting dialog with a virtual coach in eHealth applications for behavior change. Moreover, contrary to hypothesized, our observed data give credible support that participants' self-efficacy was lower after the dialog than before. These results warrant further research on how such dialogs affect self-efficacy, especially whether these lower post-measurements of self-efficacy are associated with people's more realistic assessment of their abilities. Show less
Infrared thermography (IRT) is widely used to assess skin temperature in response to physiological changes. Yet, it remains challenging to standardize skin temperature measurements over repeated... Show moreInfrared thermography (IRT) is widely used to assess skin temperature in response to physiological changes. Yet, it remains challenging to standardize skin temperature measurements over repeated datasets. We developed an open-access semi-automated segmentation tool (the IRT-toolbox) for measuring skin temperatures in the thoracic area to estimate supraclavicular brown adipose tissue (scBAT) activity, and compared it to manual segmentations. The IRT-toolbox, designed in Python, consisted of image pre-alignment and non-rigid image registration. The toolbox was tested using datasets of 10 individuals (BMI = 22.1 +/- 2.1 kg/m(2), age = 22.0 +/- 3.7 years) who underwent two cooling procedures, yielding four images per individual. Regions of interest (ROIs) were delineated by two raters in the scBAT and deltoid areas on baseline images. The toolbox enabled direct transfer of baseline ROIs to the registered follow-up images. For comparison, both raters also manually drew ROIs in all follow-up images. Spatial ROI overlap between methods and raters was determined using the Dice coefficient. Mean bias and 95% limits of agreement in mean skin temperature between methods and raters were assessed using Bland-Altman analyses. ROI delineation time was four times faster with the IRT-toolbox (01:04 min) than with manual delineations (04:12 min). In both anatomical areas, there was a large variability in ROI placement between methods. Yet, relatively small skin temperature differences were found between methods (scBAT: 0.10 degrees C, 95%LoA[-0.13 to 0.33 degrees C] and deltoid: 0.05 degrees C, 95%LoA[-0.46 to 0.55 degrees C]). The variability in skin temperature between raters was comparable between methods. The IRT-toolbox enables faster ROI delineations, while maintaining inter-user reliability compared to manual delineations. Show less
Spini, G.; Mancini, E.; Attema, T.; Abspoel, M.; Gier, J. de; Fehr, S.O.; ... ; Sloot, P.M.A. 2022
Background HIV treatment prescription is a complex process. Clinical decision support systems (CDSS) are a category of health information technologies that can assist clinicians to choose optimal... Show moreBackground HIV treatment prescription is a complex process. Clinical decision support systems (CDSS) are a category of health information technologies that can assist clinicians to choose optimal treatments based on clinical trials and expert knowledge. The usability of some CDSSs for HIV treatment would be significantly improved by using the knowledge obtained by treating other patients. This knowledge, however, is mainly contained in patient records, whose usage is restricted due to privacy and confidentiality constraints. Methods A treatment effectiveness measure, containing valuable information for HIV treatment prescription, was defined and a method to extract this measure from patient records was developed. This method uses an advanced cryptographic technology, known as secure Multiparty Computation (henceforth referred to as MPC), to preserve the privacy of the patient records and the confidentiality of the clinicians' decisions. Findings Our solution enables to compute an effectiveness measure of an HIV treatment, the average time-to-treatment-failure, while preserving privacy. Experimental results show that our solution, although at proof-of-concept stage, has good efficiency and provides a result to a query within 24 min for a dataset of realistic size. Interpretation This paper presents a novel and efficient approach HIV clinical decision support systems, that harnesses the potential and insights acquired from treatment data, while preserving the privacy of patient records and the confidentiality of clinician decisions. Show less
Poelgeest, R. van; Groningen, J.T. van; Daniels, J.H.; Roes, K.C.; Wiggers, T.; Wouters, M.W.; Schrijvers, G. 2017
