Background: To facilitate adherence to adaptive pain management behaviors after interdisciplinary multimodal pain treatment, we developed a mobile health app (AGRIPPA app) that contains two behavior regulation strategies. Objective: The aims of this project are (1) to test the effectiveness of the AGRIPPA app on pain disability; (2) to determine the cost-effectiveness; and (3) to explore the levels of engagement and usability of app users. Methods: We will perform a multicenter randomized controlled trial with two parallel groups. Within the 12-month inclusion period, we plan to recruit 158 adult patients with chronic pain during the initial stage of their interdisciplinary treatment program in one of the 6 participating centers. Participants will be randomly assigned to the standard treatment condition or to the enhanced treatment condition in which they will receive the AGRIPPA app. Patients will be monitored from the start of the treatment program until 12 months posttreatment. In our primary analysis, we will evaluate the difference over time of pain-related disability between the two conditions. Other outcome measures will include health-related quality of life, illness perceptions, pain self-efficacy, app system usage data, productivity loss, and health care expenses. Results: The study was approved by the local Medical Research Ethics Committee in October 2019. As of March 20, 2020, we have recruited 88 patients. Conclusions: This study will be the first step in systematically evaluating the effectiveness and efficiency of the AGRIPPA app. After 3 years of development and feasibility testing, this formal evaluation will help determine to what extent the app will influence the maintenance of treatment gains over time. The outcomes of this trial will guide future decisions regarding uptake in clinical practice.
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Background: Being able to care for and cope with one’s stoma adequately may significantly impact patient’s wellbeing. A well-designed mobile application (app) may improve and solve some of the difficulties patients encounter. This study aims to gain a better understanding of the problems patients face in ostomy care and to determine how to improve these problems by an app. Method: A qualitative study using six focus group interviews was conducted between March and April 2020. Patients with a stoma, representatives of patient associations and stoma-related healthcare providers participated to provide insights. A thematic content analysis method was used to analyse the transcripts. Results: Participants indicated that perioperative information could be improved, information should be applicable for all patients and the amount of stoma materials to be overwhelming. Moreover, the contact with fellow peers could be utilised more and it was unclear which healthcare provider should be contacted. All participants expected an app would be beneficial. The app should provide reliable and up-to-date information which is presented in a visually attractive manner, and facilitate peer contact in which patients can support each other. Conclusion: Adequate self-care and coping is essential for patients’ quality of life. A personalised, mobile app may be promising to overcome some of the problems related to adequate self-provision of stoma care at home, improving self-efficacy and overall well-being.
Background: In the past years, a mobile health (mHealth) app called the Dutch Talking Touch Screen Questionnaire (DTTSQ) was developed in The Netherlands. The aim of development was to enable Dutch physical therapy patients to autonomously complete a health-related questionnaire regardless of their level of literacy and digital skills. Objective: The aim of this study was to evaluate the usability (defined as the effectiveness, efficiency, and satisfaction) of the prototype of the DTTSQ for Dutch physical therapy patients with diverse levels of experience in using mobile technology. Methods: The qualitative Three-Step Test-Interview method, including both think-aloud and retrospective probing techniques, was used to gain insight into the usability of the DTTSQ. A total of 24 physical therapy patients were included. The interview data were analyzed using a thematic content analysis approach aimed at analyzing the accuracy and completeness with which participants completed the questionnaire (effectiveness), the time it took the participants to complete the questionnaire (efficiency), and the extent to which the participants were satisfied with the ease of use of the questionnaire (satisfaction). The problems encountered by the participants in this study were given a severity rating that was used to provide a rough estimate of the need for additional usability efforts. Results: All participants within this study were very satisfied with the ease of use of the DTTSQ. Overall, 9 participants stated that the usability of the app exceeded their expectations. The group of 4 average-/high-experienced participants encountered only 1 problem in total, whereas the 11 little-experienced participants encountered an average of 2 problems per person and the 9 inexperienced participants an average of 3 problems per person. A total of 13 different kind of problems were found during this study. Of these problems, 4 need to be addressed before the DTTSQ will be released because they have the potential to negatively influence future usage of the tool. The other 9 problems were less likely to influence future usage of the tool substantially. Conclusions: The usability of the DTTSQ needs to be improved before it can be released. No problems were found with satisfaction or efficiency during the usability test. The effectiveness needs to be improved by (1) making it easier to navigate through screens without the possibility of accidentally skipping one, (2) enabling the possibility to insert an answer by tapping on the text underneath a photograph instead of just touching the photograph itself, and (3) making it easier to correct wrong answers. This study shows the importance of including less skilled participants in a usability study when striving for inclusive design and the importance of measuring not just satisfaction but also efficiency and effectiveness during such studies.
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Today, embedded devices such as banking/transportation cards, car keys, and mobile phones use cryptographic techniques to protect personal information and communication. Such devices are increasingly becoming the targets of attacks trying to capture the underlying secret information, e.g., cryptographic keys. Attacks not targeting the cryptographic algorithm but its implementation are especially devastating and the best-known examples are so-called side-channel and fault injection attacks. Such attacks, often jointly coined as physical (implementation) attacks, are difficult to preclude and if the key (or other data) is recovered the device is useless. To mitigate such attacks, security evaluators use the same techniques as attackers and look for possible weaknesses in order to “fix” them before deployment. Unfortunately, the attackers’ resourcefulness on the one hand and usually a short amount of time the security evaluators have (and human errors factor) on the other hand, makes this not a fair race. Consequently, researchers are looking into possible ways of making security evaluations more reliable and faster. To that end, machine learning techniques showed to be a viable candidate although the challenge is far from solved. Our project aims at the development of automatic frameworks able to assess various potential side-channel and fault injection threats coming from diverse sources. Such systems will enable security evaluators, and above all companies producing chips for security applications, an option to find the potential weaknesses early and to assess the trade-off between making the product more secure versus making the product more implementation-friendly. To this end, we plan to use machine learning techniques coupled with novel techniques not explored before for side-channel and fault analysis. In addition, we will design new techniques specially tailored to improve the performance of this evaluation process. Our research fills the gap between what is known in academia on physical attacks and what is needed in the industry to prevent such attacks. In the end, once our frameworks become operational, they could be also a useful tool for mitigating other types of threats like ransomware or rootkits.
Structural colour (SC) is created by light interacting with regular nanostructures in angle-dependent ways resulting in vivid hues. This form of intense colouration offers commercial and industrial benefits over dyes and other pigments. Advantages include durability, efficient use of light, anti-fade properties and the potential to be created from low cost materials (e.g. cellulose fibres). SC is widely found in nature, examples include butterflies, squid, beetles, plants and even bacteria. Flavobacterium IR1 is a Gram-negative, gliding bacterium isolated from Rotterdam harbour. IR1 is able to rapidly self-assemble into a 2D photonic crystal (a form of SC) on hydrated surfaces. Colonies of IR1 are able to display intense, angle-dependent colours when illuminated with white light. The process of assembly from a disordered structure to intense hues, that reflect the ordering of the cells, is possible within 10-20 minutes. This bacterium can be stored long-term by freeze drying and then rapidly activated by hydration. We see these properties as suiting a cellular reporter system quite distinct from those on the market, SC is intended to be “the new Green Fluorescent Protein”. The ability to understand the genomics and genetics of SC is the unique selling point to be exploited in product development. We propose exploiting SC in IR1 to create microbial biosensors to detect, in the first instance, volatile compounds that are damaging to health and the environment over the long term. Examples include petroleum or plastic derivatives that cause cancer, birth defects and allergies, indicate explosives or other insidious hazards. Hoekmine, working with staff and students within the Hogeschool Utrecht and iLab, has developed the tools to do these tasks. We intend to create a freeze-dried disposable product (disposables) that, when rehydrated, allow IR1 strains to sense and report multiple hazardous vapours alerting industries and individuals to threats. The data, visible as brightly coloured patches of bacteria, will be captured and quantified by mobile phone creating a system that can be used in any location by any user without prior training. Access to advice, assay results and other information will be via a custom designed APP. This work will be performed in parallel with the creation of a business plan and market/IP investigation to prepare the ground for seed investment. The vision is to make a widely usable series of tests to allow robust environmental monitoring for all to improve the quality of life. In the future, this technology will be applied to other areas of diagnostics.
Within the film and theater world, special effects make-up is used to adapt the appearance of actors for visual storytelling. Currently the creation of special effects makeup is a time-consuming process which creates a lot of waste that doesn’t fit in with the goals of a sustainable industry. Combine with the trend of the digitization of the movie and theater industry which require faster and more iterative workflows, the current ways of creating special effects makeup requires changing. Within this project we would like to explore if the traditional way of working can be converted to a digital production process. Our research consists of three parts. Firstly, we would like to explore if a mobile face scanning rig can be used to create digital copies of actors, and such eliminate the need to creates molds. Secondly, we would like to see if digital sculpting can replace the traditional methods of sculpting molds, casts and prosthetics. Here we would like to compare both methods in terms of creativity and time consumption. The third part of our project will be to explore the use of 3D printing for the creation of molds and prosthetics.
