This study investigates the degree of news avoidance during the first months of the Covid-19 pandemic in the Netherlands. Based on two panel surveys conducted in the period April–June 2020, this study shows that the increased presence of this behavior, can be explained by negative emotions and feelings the news causes by citizens. Moreover, news avoidance indeed has a positive effect on perceived well-being. These findings point to an acting balance for individual news consumers. In a pandemic such as Covid-19 news consumers need to be informed, but avoiding news is sometimes necessary to stay mentally healthy.
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It has become increasingly clear that news avoidance is a multidimensional phenomenon consisting of both intentional news avoidance and low news use, yet knowledge about the longitudinal dynamics between these dimensions is still lacking. Furthermore, there is a lack of studies investigating the relationship between intentional news avoidance and specific news media repertoires. This article contributes to the literature on news avoidance by (a) including measures of both intentional news avoidance and news consumption as well as (b) using longitudinal panel data, to investigate the long-term dynamics between news media repertoires and intentional news avoidance. We rely on a four-wave panel survey conducted in Sweden (N = 7,283). The results show that intentional news avoidance and low news use are indeed distinct but intertwined dimensions. Intentional news avoidance is dynamic and influenced by different situational and media environmental factors and can be viewed as a function of (reconstructing) news consumption practices. At the same time, the results also show that people who report that they intentionally avoid the news are more likely to become low news users, implying that for some, temporary intentional avoidance might lead to habitual estrangement.
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Lower levels of news use are generally understood to be associated with less political engagement among citizens. But while some people simply have a low preference for news, others avoid the news intentionally. So far little is known about the relationship between active news avoidance and civic engagement in society, a void this study has set out to fill. Based on a four-wave general population panel survey in the Netherlands, conducted between April and July 2020 (N = 1,084) during a crisis situation, this research-in-brief investigates the development of news avoidance and pro-social civic engagement over time. Results suggest that higher news topic avoidance results in higher levels of civic engagement. The study discusses different explanations for why less news can mean more engagement.
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With the increased adoption of real-time objective measurements of player experience, advances have been made in characterising the dynamically changing aspects of the player experience during gameplay itself. A direct coupling to player action, however, is not without challenges. Many physiological responses, for instance, have an inherent delay, and often take some time to return to a baseline, providing challenges of interpretation when analysing rapidly changing gameplay on a micro level of interaction. The development of event-related, or phasic, measurements directly coupled to player actions provides additional insights, for instance through player modelling, but also through the use of behavioural characteristics of the human computer interaction itself. In this study, we focused on the latter, and measured keyboard pressure in a number of different, fast-paced action games. In this particular case, we related specific functional game actions (keyboard presses) to experiential player behaviour. We found keyboard pressure to be higher for avoidance as compared to approach-oriented actions. Additionally, the difference between avoidance and approach keyboard pressure related to levels of arousal. The findings illustrate the application potential of qualifying players’ functional actions at play (navigating in a game) and interpret player experience related to these actions through players’ real world behavioural characteristics like interface pressure.
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Background: Recent theoretical models emphasize the role of impulsive processes in alcohol addiction, which can be retrained with computerized Cognitive Bias Modification (CBM) training. In this study, the focus is on action tendencies that are activated relatively automatically. Objective: The aim of the study is to examine the effectiveness of online CBM Alcohol Avoidance Training using an adapted Approach-Avoidance Task as a supplement to treatment as usual (TAU) in an outpatient treatment setting. Methods: The effectiveness of 8 online sessions of CBM Alcohol Avoidance Training added to TAU is tested in a double-blind, randomized controlled trial with pre- and postassessments, plus follow-up assessments after 3 and 6 months. Participants are adult patients (age 18 years or over) currently following Web-based or face-to-face TAU to reduce or stop drinking. These patients are randomly assigned to a CBM Alcohol Avoidance or a placebo training. The primary outcome measure is a reduction in alcohol consumption. We hypothesize that TAU + CBM will result in up to a 13-percentage point incremental effect in the number of patients reaching the safe drinking guidelines compared to TAU + placebo CBM. Secondary outcome measures include an improvement in health status and a decrease in depression, anxiety, stress, and possible mediation by the change in approach bias. Finally, patients’ adherence, acceptability, and credibility will be examined. Results: The trial was funded in 2014 and is currently in the active participant recruitment phase (since May 2015). Enrolment will be completed in 2019. First results are expected to be submitted for publication in 2020. Conclusions: The main purpose of this study is to increase our knowledge about the added value of online Alcohol Avoidance Training as a supplement to TAU in an outpatient treatment setting. If the added effectiveness of the training is proven, the next step could be to incorporate the intervention into current treatment.
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Background: Alcohol use is associated with an automatic tendency to approach alcohol, and the retraining of this tendency (cognitive bias modification [CBM]) shows therapeutic promise in clinical settings. To improve access to training and to enhance participant engagement, a mobile version of alcohol avoidance training was developed.Objective: The aims of this pilot study were to assess (1) adherence to a mobile health (mHealth) app; (2) changes in weekly alcohol use from before to after training; and (3) user experience with regard to the mHealth app.Methods: A self-selected nonclinical sample of 1082 participants, who were experiencing problems associated with alcohol, signed up to use the alcohol avoidance training app Breindebaas for 3 weeks with at least two training sessions per week. In each training session, 100 pictures (50 of alcoholic beverages and 50 of nonalcoholic beverages) were presented consecutively in a random order at the center of a touchscreen. Alcoholic beverages were swiped upward (away from the body), whereas nonalcoholic beverages were swiped downward (toward the body). During approach responses, the picture size increased to mimic an approach movement, and conversely, during avoidance responses, the picture size decreased to mimic avoidance. At baseline, we assessed sociodemographic characteristics, alcohol consumption, alcohol-related problems, use of other substances, self-efficacy, and craving. After 3 weeks, 37.89% (410/1082) of the participants (posttest responders) completed an online questionnaire evaluating adherence, alcohol consumption, and user satisfaction. Three months later, 19.03% (206/1082) of the participants (follow-up responders) filled in a follow-up questionnaire examining adherence and alcohol consumption.Results: The 410 posttest responders were older, were more commonly female, and had a higher education as compared with posttest dropouts. Among those who completed the study, 79.0% (324/410) were considered adherent as they completed four or more sessions, whereas 58.0% (238/410) performed the advised six or more training sessions. The study identified a significant reduction in alcohol consumption of 7.8 units per week after 3 weeks (95% CI 6.2-9.4, P<.001; n=410) and another reduction of 6.2 units at 3 months for follow-up responders (95% CI 3.7-8.7, P<.001; n=206). Posttest responders provided positive feedback regarding the fast-working, simple, and user-friendly design of the app. Almost half of the posttest responders reported gaining more control over their alcohol use. The repetitious and nonpersonalized nature of the intervention was suggested as a point for improvement.Conclusions: This is one of the first studies to employ alcohol avoidance training in a mobile app for problem drinkers. Preliminary findings suggest that a mobile CBM app fulfils a need for problem drinkers and may contribute to a reduction in alcohol use. Replicating these findings in a controlled study is warranted.
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Current practice regarding risk assessment contemplates the severity and likelihood of risks and employs the use of matrices where these factors are classified and cross-referenced to evaluate risk levels. Depending on the adequacy and reliability of data, the likelihood is estimated with quantitative or qualitative methods; severity is estimated according to experience from past events. This standard technique for assessing risks has been negatively criticised regarding validity and reliability due to effects of cognitive biases and a deterministic view of the possible consequences of risks. Even more, because of the lack of standardisation in risk matrices, a benchmarking across systems and organisations is not feasible. Taking into account the limitations mentioned, as well as the fact that the classification of hazards/causal factors, risk event(s) and consequences always depend on the analyst's view, this study proposes the Safety Risk Avoidance Capability (SAREAC) metric for a defined system. This metric focus on the prevention of risk events and combines quantitative and qualitative parameters referred in the literature but not yet exploited. SAREAC consists of two parts: the influence of hazards and the remaining effects of hazards after implementing or designing controls. Each of the SAREAC parts is calculated through specific steps which they result in a normalized score that allows more reliable comparisons amongst systems or over time. Data from a published risk assessment case study were used to demonstrate the use of SAREAC.
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The number of people that intentionally avoid the news is growing. This could have several personal and societal implications. Previous research exposed various motives to avoid news, which lead to different manifestations of news avoidance, and consequently different implications. However, so far less is known about the differences in news avoidance types. In this study, we aim to explore different profiles of news avoiders beyond demographics, based on their motives to avoid news, values in life and personality traits. We analyze how this relates to background characteristics, the degree of news avoidance (occasional, regular, consistent), and news consumption. We rely on a survey conducted in The Netherlands (N = 2798) in March 2022. We conducted a Latent Profile Analysis and found seven news avoiders’ profiles: (1) interested occasional avoider; (2) emotive occasional avoider; (3) critical occasional avoider; (4) status-driven occasional avoider; (5) skeptical frequent avoider; (6) news outsider; and (7) convinced frequent avoider. This provides a nuanced picture of news avoidance.
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Adults of many mosquito species feed on plants to obtain metabolic energy and to enhance reproduction. Mosquitoes primarily rely on olfaction to locate plants and are known to respond to a range of plant volatiles. We studied the olfactory response of the yellow fever mosquito Aedes aegypti to methyl jasmonate (MeJA) and cis-jasmone (CiJA), volatile compounds originating from the octadecanoid signaling pathway that plays a key role in plant defense against herbivores. Specifcally, we investigated how Ae. aegypti of diferent ages responded to elevated levels of CiJA in two attractive odor contexts, either derived from Lima bean plants or human skin. Aedes aegypti females landed signifcantly less often on a surface with CiJA and MeJA compared to the solvent control, CiJA exerting a stronger reduction in landing than MeJA. Odor context (plant or human) had no signifcant main efect on the olfactory responses of Ae. aegypti females to CiJA. Mosquito age signifcantly afected the olfactory response, older females (7–9 d) responding more strongly to elevated levels of CiJA than young females (1–3 d) in either odor context. Our results show that avoidance of CiJA by Ae. aegypti is independent of odor background, suggesting that jasmonates are inherently aversive cues to these mosquitoes. We propose that avoidance of plants with elevated levels of jasmonates is adaptive to mosquitoes to reduce the risk of encountering predators that is higher on these plants, i.e. by avoiding ‘enemy-dense-space’.
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The real-time simulation of human crowds has many applications. In a typical crowd simulation, each person ('agent') in the crowd moves towards a goal while adhering to local constraints. Many algorithms exist for specific local ‘steering’ tasks such as collision avoidance or group behavior. However, these do not easily extend to completely new types of behavior, such as circling around another agent or hiding behind an obstacle. They also tend to focus purely on an agent's velocity without explicitly controlling its orientation. This paper presents a novel sketch-based method for modelling and simulating many steering behaviors for agents in a crowd. Central to this is the concept of an interaction field (IF): a vector field that describes the velocities or orientations that agents should use around a given ‘source’ agent or obstacle. An IF can also change dynamically according to parameters, such as the walking speed of the source agent. IFs can be easily combined with other aspects of crowd simulation, such as collision avoidance. Using an implementation of IFs in a real-time crowd simulation framework, we demonstrate the capabilities of IFs in various scenarios. This includes game-like scenarios where the crowd responds to a user-controlled avatar. We also present an interactive tool that computes an IF based on input sketches. This IF editor lets users intuitively and quickly design new types of behavior, without the need for programming extra behavioral rules. We thoroughly evaluate the efficacy of the IF editor through a user study, which demonstrates that our method enables non-expert users to easily enrich any agent-based crowd simulation with new agent interactions.
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