Effectiveness of a web-based intervention aimed at healthy dietary and physical activity behavior: a randomized controlled trial about users and usage

Background:\ud Recent studies have shown the potential of Web-based interventions for changing dietary and physical activity (PA) behavior. However, the pathways of these changes are not clear. In addition, nonusage poses a threat to these interventions. Little is known of characteristics of participants that predict usage.\ud \ud Objective:\ud In this study we investigated the users and effect of the Healthy Weight Assistant (HWA), a Web-based intervention aimed at healthy dietary and PA behavior. We investigated the value of a proposed framework (including social and economic factors, condition-related factors, patient-related factors, reasons for use, and satisfaction) to predict which participants are users and which participants are nonusers. Additionally, we investigated the effectiveness of the HWA on the primary outcomes, self-reported dietary and physical activity behavior.\ud \ud Methods:\ud Our design was a two-armed randomized controlled trial that compared the HWA with a waiting list control condition. A total of 150 participants were allocated to the waiting list group, and 147 participants were allocated to the intervention group. Online questionnaires were filled out before the intervention period started and after the intervention period of 12 weeks. After the intervention period, respondents in the waiting list group could use the intervention. Objective usage data was obtained from the application itself.\ud \ud Results:\ud In the intervention group, 64% (81/147) of respondents used the HWA at least once and were categorized as “users.” Of these, 49% (40/81) used the application only once. Increased age and not having a chronic condition increased the odds of having used the HWA (age: beta = 0.04, P = .02; chronic condition: beta = 2.24, P = .003). Within the intervention group, users scored better on dietary behavior and on knowledge about healthy behavior than nonusers (self-reported diet: χ22 = 8.4, P = .02; knowledge: F1,125 = 4.194, P = .04). Furthermore, users underestimated their behavior more often than nonusers, and nonusers overestimated their behavior more often than users (insight into dietary behavior: χ22 = 8.2, P = .02). Intention-to-treat analyses showed no meaningful significant effects of the intervention. Exploratory analyses of differences between pretest and posttest scores of users, nonusers, and the control group showed that on dietary behavior only the nonusers significantly improved (effect size r = −.23, P = .03), while on physical activity behavior only the users significantly improved (effect size r = −.17, P = .03).\ud \ud Conclusions:\ud Respondents did not use the application as intended. From the proposed framework, a social and economic factor (age) and a condition-related factor (chronic condition) predicted usage. Moreover, users were healthier and more knowledgeable about healthy behavior than nonusers. We found no apparent effects of the intervention, although exploratory analyses showed that choosing to use or not to use the intervention led to different outcomes. Combined with the differences between groups at baseline, this seems to imply that these groups are truly different and should be treated as separate entities

EUREGIO MRSA-net Twente/Munsterland - a Dutch-German cross-border network for the prevention and control of infections caused by methicillin-resistant Staphylococcus aureus

Binary file ES_Abstracts_Final_ECDC.txt matches </jats:p

Wat komt u hier doen? Terug in Obunga

In 2050 zullen er in de Afrikaanse steden naar schatting 1,3 miljard mensen wonen, tweemaal zoveel als in heel Europa. Deze steden ontwikkelen zich vanuit een geheel eigen dynamiek. De stad Kisumu in Kenia telt in 2018 700.000 inwoners, waarvan er 550.000 in krottenwijken wonen. De informele straateconomie beheerst de openbare ruimte en levert de meeste werkgelegenheid. Bijna de helft van de mensen leeft onder de absolute armoedegrens. In zijn onderzoek richt Rob van Gemert zich op Obunga, een wijk van Kisumu. Hij schetst een beeld van het wonen en werken in deze krottenwijk. Samen met de bewoners zoekt hij naar mogelijkheden om de wijk te verbeteren. Terwijl hij door de wijk loopt, rondkijkt, luistert en vergadert, vormt zich een integraal plan. De eigenheid van de wijk vormt hierbij het uitgangspunt; niet als probleem, maar juist als oplossing. Dan presenteert het stadsbestuur een stedenbouwkundig plan, ontworpen door Franse adviseurs. Ze hebben een nieuw imago voor het centrum bedacht, negeren de straateconomie volledig en willen alle krottenwijken ombouwen tot woongebieden voor de middenklasse. “Niemand luistert naar ons”, zeggen de mensen in Obunga.Wetensch. publicati

Single Shot Temporal Action Detection

Temporal action detection is a very important yet challenging problem, since videos in real applications are usually long, untrimmed and contain multiple action instances. This problem requires not only recognizing action categories but also detecting start time and end time of each action instance. Many state-of-the-art methods adopt the "detection by classification" framework: first do proposal, and then classify proposals. The main drawback of this framework is that the boundaries of action instance proposals have been fixed during the classification step. To address this issue, we propose a novel Single Shot Action Detector (SSAD) network based on 1D temporal convolutional layers to skip the proposal generation step via directly detecting action instances in untrimmed video. On pursuit of designing a particular SSAD network that can work effectively for temporal action detection, we empirically search for the best network architecture of SSAD due to lacking existing models that can be directly adopted. Moreover, we investigate into input feature types and fusion strategies to further improve detection accuracy. We conduct extensive experiments on two challenging datasets: THUMOS 2014 and MEXaction2. When setting Intersection-over-Union threshold to 0.5 during evaluation, SSAD significantly outperforms other state-of-the-art systems by increasing mAP from 19.0% to 24.6% on THUMOS 2014 and from 7.4% to 11.0% on MEXaction2.Comment: ACM Multimedia 201