Snow Control - An RCT protocol for a web-based self-help therapy to reduce cocaine consumption in problematic cocaine users

Background: Cocaine use has increased in most European countries, including Switzerland, and many states worldwide. The international literature has described treatment models that target the general population. In addition to supplying informative measures at the level of primary and secondary prevention, the literature also offers web-based self-help tools for problematic substance users, which is in line with tertiary prevention. Such programs, however, have been primarily tested on individuals with problematic alcohol and cannabis consumption, but not on cocaine-dependent individuals. Methods/Design: This paper presents the protocol of a randomised clinical trial to test the effectiveness of a web-based self-help therapy to reduce cocaine use in problematic cocaine users. The primary outcome is severity of cocaine dependence. Secondary outcome measures include cocaine craving, consumption of cocaine and other substances of abuse in the past month, and changes in depression characteristics. The therapy group will receive a 6-week self-help therapy to reduce cocaine consumption based on methods of Cognitive Behavioural Therapy, principles of Motivational Interviewing and self-control practices. The control group will be presented weekly psycho-educative information with a quiz. The predictive validity of participant characteristics on treatment retention and outcome will be explored. Discussion: To the best of our knowledge, this will be the first randomised clinical trial to test the effectiveness of online self-help therapy to reduce or abstain from cocaine use. It will also investigate predictors of outcome and retention. This trial is registered at Current Controlled Trials and is traceable as NTR-ISRCTN93702927

Educational Theories and Learning Analytics: From Data to Knowledge: The Whole Is Greater Than the Sum of Its Parts

The study of learning is grounded in theories and research. Since learning is complex and not directly observable, it is often inferred by collecting and analysing data based on the things learners do or say. By virtue, theories are developed from the analyses of data collected. With the proliferation of technology, large amounts of data are generated when students learn online. Therefore, researchers not only have data on students’ learning performance, but they also have data on the actions students take to achieve the desired learning outcomes. These data could help researchers to understand how students learn and the conditions needed for successful learning. In turn, the information can be translated to instructional and learning design to support students. The aim of the chapter is to discuss how learning theories and learning analytics are important components of educational research. To achieve this aim, studies employing learning analytics are qualitatively reviewed to examine which theories have been used and how the theories have been investigated. The results of the review show that self-regulated learning, motivation, and social constructivism theories were used in studies employing learning analytics. However, the studies at present are mostly correlational. Therefore, experimental studies are needed to examine how theory-informed practices can be implemented so that students can be better supported in online learning environments. The chapter concludes by proposing an iterative loop for educational research employing learning analytics in which learning theories guide data collection and analyses. To convert data into knowledge, it is important to recognize what we already know and what we want to examine.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Web Information System