Alcohol consumption in Slovenia is one of the highest in Europe. In Slovenia there were a few epidemiological studies on drinking habits among adult population, but none of them has used the AUDIT ...questionnaire or the Internet for research.
The aim of this study was to analyse the drinking habits of the visitors of our website www.nalijem.si, which included an anonymous questionnaire for self-assessment of alcohol drinking.
A cross sectional survey was conducted between January 2010 and December 2013. The front page of our website included an invitation to fill in the anonymous web-based questionnaire; a part of it was the AUDIT 10 questionnaire. Everyone who filled in the questionnaire completely received an individualized feedback on his drinking.
54.020 persons visited our website, 15.817 (29.3%) of them started to fill in the questionnaire, 12.800 (80.9%) filled it in completely. In the analysis, 9.087 (71.0%) persons were included who completed the questionnaire for themselves. There were 37.1% (N=3.373) women and 62.9% (N=5.714) men. The average age was 33 years, the majority was employed (59.7%, N=5.222). The minority drank alcohol 2-4 times per month (32.8%, N=2.977) and most of them (64.5%, N=5.869) drank more than 3 units of alcohol per one occasion on a typical day. The average AUDIT 10 score was 11.7 for men, 8.1 for women.
A large percentage of participants were identified as hazardous and harmful drinkers, which should be a matter of serious concern.
A two-fold personalized feedback mechanism is established for consensus reaching in social network group decision-making (SN-GDM). It consists of two stages: 1) generating the trusted recommendation ...advice for individuals and 2) producing a a personalized adoption coefficient for reducing unnecessary adjustment costs. A uninorm interval-valued trust propagation operator is developed to obtain an indirect trust relationship, which is used to generate personalized recommendation advice based on the principle of "a recommendation being more acceptable the higher the level of trust it derives from." An optimization model is built to minimize the total adjustment cost of reaching consensus by determining the personalized feedback adoption coefficient based on individuals' consensus levels. Consequently, the proposed two-fold personalized feedback mechanism achieves a balance between group consensus and individual personality. An example to demonstrate how the proposed two-fold personalized feedback mechanism works is included, which is also used to show its rationality by comparing it with the traditional feedback mechanism in group decision making (GDM).
Different feedback mechanisms have been reported in consensus reaching models to provide advices for preference adjustment to assist decision makers to improve their consensus levels. However, most ...feedback mechanisms do not consider the willingness of decision makers to accept these advices. In the opinion dynamics discipline, the bounded confidence model justifies well that in the process of interaction a decision maker only considers the preferences that do not exceed a certain confidence level compared to his own preference. Inspired by this idea, this article proposes a new consensus reaching model with personalized feedback mechanism to help decision makers with bounded confidences in achieving consensus. Specifically, the personalized feedback mechanism produces more acceptable advices in the two cases where bounded confidences are known or unknown, and the unknown ones are estimated by a learning algorithm. Finally, numerical example and simulation analysis are presented to explore the effectiveness of the proposed model in reaching consensus.
Athletes are exposed to various psychological and physiological stressors, such as losing matches and high training loads. Understanding and improving the resilience of athletes is therefore crucial ...to prevent performance decrements and psychological or physical problems. In this review, resilience is conceptualized as a dynamic process of bouncing back to normal functioning following stressors. This process has been of wide interest in psychology, but also in the physiology and sports science literature (e.g. load and recovery). To improve our understanding of the process of resilience, we argue for a collaborative synthesis of knowledge from the domains of psychology, physiology, sports science, and data science. Accordingly, we propose a multidisciplinary, dynamic, and personalized research agenda on resilience. We explain how new technologies and data science applications are important future trends (1) to detect warning signals for resilience losses in (combinations of) psychological and physiological changes, and (2) to provide athletes and their coaches with personalized feedback about athletes' resilience.
This paper explores and rehabilitates the value of decisional privacy as a conceptual tool, complementary to informational privacy, for critiquing personalized choice architectures employed by ...self-tracking technologies. Self-tracking technologies are promoted and used as a means to self-improvement. Based on large aggregates of personal data and the data of other users, self-tracking technologies offer personalized feedback that nudges the user into behavioral change. The real-time personalization of choice architectures requires continuous surveillance and is a very powerful technology, recently coined as “hypernudging.” While users celebrate the increased personalization of their coaching devices, “hypernudging” technologies raise concerns about manipulation. This paper addresses that intuition by claiming that decisional privacy is at stake. It thus counters the trend to solely focus on informational privacy when evaluating information and communication technologies. It proposes that decisional privacy and informational privacy are often part of a mutually reinforcing dynamic. Hypernudging is used as a key example to illustrate that the two dimensions should not be treated separately. Hypernudging self-tracking technologies compromise autonomy because they violate informational and decisional privacy. In order to effectively judge whether technologies that use hypernudges empower users, we need both privacy dimensions as conceptual tools.
Digital learning technologies offer many opportunities to personalize instruction and learning in K-12 and higher education. In the last ten years, a growing body of research described personalized ...feedback implementations and investigated their effects on educational outcomes. Building on personalized education and adaptive learning systems models, this review provides an analytic framework to summarize key features of personalized feedback implementations and main empirical results. The systematic literature search resulted in 39 studies published in the last ten years. We found that scholars developed and investigated personalized feedback on the microscale, mesoscale, and macroscale of digital learning environments. However, the adaptive sources (To what is feedback adapted?) are mainly restricted to the current knowledge level and learning behavior data. Other interesting data sources for feedback adaptation remain underresearched, e.g., emotional state measures, progress measures, learning goals, or personality traits. Only a minority of the reviewed studies provided an empirical or theoretical rationale for assigning feedback messages to different types of students. Most studies report positive or at least mixed or neutral effects of personalized feedback on educational outcomes. This review discusses several implications for future directions in research on digitalized and personalized feedback. This study also adds to previous literature reviews on automatic and adaptive feedback that did not clearly distinguish task-adaptiveness and student-adaptiveness in digital feedback examples.
Ecological Momentary Assessment (EMA) in which participants report on their moment-to-moment experiences in their natural environment, is a hot topic. An emerging field in clinical psychology based ...on either EMA, or what we term
(ERA) as it requires retrospectivity, is the field of
. In this field, EMA/ERA-data-driven summaries are presented to participants with the goal of promoting their insight in their experiences. Underlying this procedure are some fundamental assumptions about (i) the relation between true moment-to-moment experiences and retrospective evaluations of those experiences, (ii) the translation of these experiences and evaluations to different types of data, (iii) the comparison of these different types of data, and (iv) the impact of a summary of moment-to-moment experiences on retrospective evaluations of those experiences. We argue that these assumptions deserve further exploration, in order to create a strong evidence-based foundation for the personalized feedback procedure.
Mastery assessments are used in many digital learning environments to control learning progression and support low-achieving students relearning important content. But research on personalized ...feedback following a mastery assessment is scarce and yielded ambiguous effects. Therefore, this study seeks to contribute to this area of research by investigating the effect of two different feedback messages in short online courses for German and English language grammar and spelling in secondary classrooms (grades 6–10). The study compares a reward-based feedback message to a self-referenced feedback message. The reward-based message indicates if the learner reaches the mastery criterion and how many points the learning app awarded for completing the test. The self-referenced feedback message applies motivation theory to strengthen students' internal attribution of causes for the test performance. The web-app MasteryX (www.masteryx.de) randomly assigned students to either the reward-based or the self-referenced feedback message. The study sampled 620 students (309 female, 311 male) in 53 classrooms from 27 secondary schools. It analyzed the effect of the two types of feedback messages on the level of test-retest-sequences (n = 2450). Results indicate small though significant positive effects of the self-referenced feedback message on subsequent learning behavior (reading elaborated item feedback, training behavior). However, a multilevel regression model showed small to medium effects of the reward-based feedback message on the higher course levels' follow-up mastery assessment score. The findings emphasize the complexity of designing personalized feedback strategies in online learning environments with mastery assessments.
•Effects of reward-based vs. self-referenced feedback messages are compared in a randomized controlled trial.•Data analyses on a fine-grained level of test-retest-sequences in mastery learning-based courses.•Self-referenced feedback message positively affects elaborated feedback reading time and training.•Reward-based feedback message has medium achievement effect in higher course levels.
Objective:
Suicide is the second leading cause of death among college students in the United States, and the percentage of students reporting suicidal thoughts is increasing. Nevertheless, many ...students at risk do not seek mental health (MH) services. This randomized controlled trial (RCT) examined the efficacy of Electronic Bridge to Mental Health for College Students (eBridge) for increasing at-risk students' linkage to MH services.
Method:
Students from four universities were recruited via email; 40,347 (22.6%) completed the online suicide risk screen; and 3,363 (8.3%) met criteria for randomization based on suicide risk factors and lack of current treatment (62.2% female, 35.0% male, 2.8% transgender/nonbinary; 73.2% White, 7.0% Black, 19.9% Asian, 11.7% other; 12.4% Hispanic, 76.2% undergraduate). These students were randomized to eBridge personalized feedback (PF) with option of online counseling or Control (PF). The primary outcome was linkage to MH services within 6 months.
Results:
Among students assigned to eBridge, 355 students (21.0%) posted ≥1 message, and 168 (10.0%) posted ≥2 messages to the counselor. In intent-to-treat analyses, there was no eBridge effect on obtaining MH services. However, within the eBridge group, students who posted ≥1 message were significantly more likely to link to MH services.
Conclusions: eBridge shows promise for reaching a relatively small subset of college students at risk for suicide; however, engagement in eBridge was low. This study underscores the urgent need for more effective strategies to engage young adults in online mental health interventions.
What is the public health significance of this article?
Suicide is the second leading cause of death among college students. Moreover, recent national surveys indicate that more than 10% of college students have seriously considered attempting suicide within the past year. In keeping with recommendations in the National Strategy for Suicide Prevention (Office of the Surgeon General & National Action Alliance for Suicide Prevention, 2012), this project examined the efficacy of eBridge, an online intervention that identifies students at elevated suicide risk and facilitates their linkage to mental health services, in a multiuniversity randomized controlled trial.
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