How to convince the vaccine‐hesitant? : An ease‐of‐access nudge, but not risk‐related information increased Covid vaccination‐related behaviors in the unvaccinated
2023-08-08, Giese, Helge, Neth, Hansjörg, Wegwarth, Odette, Gaissmaier, Wolfgang, Stok, F. Marijn
In this study, we contrast how different benefit and harm information formats and the presence or absence of an ease‐of‐access nudge may facilitate COVID vaccination uptake for a sample of 620 unvaccinated Dutch adults at a timepoint when the vaccine had been widely available for more than a month. Using a 2 × 2 between‐subjects factorial design, we varied the information format on mRNA COVID vaccination statistics (generic text vs. facts box) and an affirmative nudge emphasizing the ease of making a vaccination appointment (absent vs. present). We assessed the acceptance of the vaccination information provided, perceptions on the vaccination, and whether participants directly visited a COVID vaccination appointment website. Whereas the facts box did not significantly affect participants' information acceptance, vaccination attitudes, intentions, and link clicking, the affirmative nudge alongside an online link systematically increased the likelihood of clicking on the link to make a vaccination appointment. A verbal nudge emphasizing the ease of vaccine accessibility is more likely to increase vaccination uptake in an unvaccinated population than informational campaigns on vaccine effectiveness.
Task-based Visual Interactive Modeling : Decision Trees and Rule-based Classifiers
2021-01-13, Streeb, Dirk, Metz, Yannick, Schlegel, Udo, Schneider, Bruno, El-Assady, Mennatallah, Neth, Hansjörg, Chen, Min, Keim, Daniel A.
Visual analytics enables the coupling of machine learning models and humans in a tightly integrated workflow, addressing various analysis tasks. Each task poses distinct demands to analysts and decision-makers. In this survey, we focus on one canonical technique for rule-based classification, namely decision tree classifiers. We provide an overview of available visualizations for decision trees with a focus on how visualizations differ with respect to 16 tasks. Further, we investigate the types of visual designs employed, and the quality measures presented. We find that (i) interactive visual analytics systems for classifier development offer a variety of visual designs, (ii) utilization tasks are sparsely covered, (iii) beyond classifier development, node-link diagrams are omnipresent, (iv) even systems designed for machine learning experts rarely feature visual representations of quality measures other than accuracy. In conclusion, we see a potential for integrating algorithmic techniques, mathematical quality measures, and tailored interactive visualizations to enable human experts to utilize their knowledge more effectively.
Die Rolle von Kognitionen beim sozialen Einfluss von Freunden auf den Alkoholkonsum in einem Erstsemesternetzwerk
2019-08-23, Giese, Helge, Neth, Hansjörg, Gaissmaier, Wolfgang
In psychologischen Theorien zur Gesundheitsverhaltensförderung nehmen soziale Konstrukte, wie z.B. Normwahrnehmung, einen zentralen Platz ein. Das tatsächliche Verhalten in sozialen Kontexten wird dabei oft außer Acht gelassen. In diesem Vortrag wird daher darauf eingegangen, inwiefern Normwahrnehmungen innerhalb eines sozialen Netzwerks soziale Einflüsse beim Alkoholkonsum erklären können.
109 Psychologiestudierende wurden zu drei Messzeitpunkten innerhalb des ersten Semesters zu ihren alkoholbezogenen Kognitionen, Alkoholkonsum und Freunden innerhalb des Semesters befragt. Zur Vorhersage sozialer Einflüsse auf Alkoholkonsum und Freundschaftsentwicklungen wurden RSiena Modelle angewandt.
Der durchschnittliche Alkoholkonsum von Freunden im Semester sagte den Konsum zum nächsten Messzeitpunkt auch nach der Kontrolle von Kognitionen, wie der Wahrnehmung vom Verhalten der Freunde, vorher (b = 1,89, OR = 6,64, 95%CI [1,28; 34,50], p = 0,022).
Soziale Einflüsse beim Alkoholkonsum von Erstsemestern können nicht vollständig durch kognitive Konstrukte wie Normwahrnehmungen aufgeklärt werden. Dies suggeriert, dass es zusätzliche soziale Kontexteinflüsse gibt.
Visual Working Memory Resources Are Best Characterized as Dynamic, Quantifiable Mnemonic Traces
2017, Veksler, Bella Z., Boyd, Rachel, Myers, Christopher W., Gunzelmann, Glenn, Neth, Hansjörg, Gray, Wayne D.
Visual working memory (VWM) is a construct hypothesized to store a small amount of accurate perceptual information that can be brought to bear on a task. Much research concerns the construct's capacity and the precision of the information stored. Two prominent theories of VWM representation have emerged: slot-based and continuous-resource mechanisms. Prior modeling work suggests that a continuous resource that varies over trials with variable capacity and a potential to make localization errors best accounts for the empirical data. Questions remain regarding the variability in VWM capacity and precision. Using a novel eye-tracking paradigm, we demonstrate that VWM facilitates search and exhibits effects of fixation frequency and recency, particularly for prior targets. Whereas slot-based memory models cannot account for the human data, a novel continuous-resource model does capture the behavioral and eye tracking data, and identifies the relevant resource as item activation.
Communicating for the Safe Use of Medicines : Progress and Directions for the 2020s Promoted by the Special Interest Group of the International Society of Pharmacovigilance
2023, Bahri, Priya, Bowring, Geoffrey, Edwards, Brian D., Anton, Christopher, Aronson, Jeffrey K., Caro-Rojas, Angela, Hugman, Bruce P. J., Mol, Peter G., Gaissmaier, Wolfgang, Neth, Hansjörg
Determinants of information diffusion in online communication on vaccination : The benefits of visual displays
2021, Giese, Helge, Neth, Hansjörg, Gaissmaier, Wolfgang
Social media are an increasingly important source of information on the benefits and risks of vaccinations, but the high prevalence of misinformation provides challenges for informed vaccination decisions. It is therefore important to understand which messages are likely to diffuse online and why, and how relevant aspects—such as scientific facts on vaccination effectiveness—can be made more comprehensible and more likely to be shared. In two studies, we (i) explore which characteristics of messages on flu vaccination facilitate their diffusion in online communication, and (ii) whether visual displays (i.e., icon arrays) facilitate the comprehension and diffusion of scientific effectiveness information.
In Study 1, 208 participants each rated a random sample of 15 out of 63 messages on comprehensibility, trustworthiness, persuasiveness, familiarity, informativeness, valence, and arousal, and then reported which information they would share with subsequent study participants. In Study 2 (N = 758), we employed the same rating procedure for a selected set of 9 messages and experimentally manipulated how scientific effectiveness information was displayed.
Study 1 illustrated that scientific effectiveness information was difficult to understand and thus did not diffuse well. Study 2 demonstrated that visual displays improved the understanding of this information, which could, in turn, increase its social impact.
The comprehensibility of scientific information is an important prerequisite for its diffusion. Visual displays can facilitate informed vaccination decisions by rendering important information on vaccination effectiveness more transparent and increasing the willingness to share this information.
Perspectives on the 2×2 Matrix : Solving Semantically Distinct Problems Based on a Shared Structure of Binary Contingencies
2021-02-09, Neth, Hansjörg, Gradwohl, Nico, Streeb, Dirk, Keim, Daniel A., Gaissmaier, Wolfgang
Cognition is both empowered and limited by representations. The matrix lens model explicates tasks that are based on frequency counts, conditional probabilities, and binary contingencies in a general fashion. Based on a structural analysis of such tasks, the model links several problems and semantic domains and provides a new perspective on representational accounts of cognition that recognizes representational isomorphs as opportunities, rather than as problems. The shared structural construct of a 2×2 matrix supports a set of generic tasks and semantic mappings that provide a unifying framework for understanding problems and defining scientific measures. Our model's key explanatory mechanism is the adoption of particular perspectives on a 2×2 matrix that categorizes the frequency counts of cases by some condition, treatment, risk, or outcome factor. By the selective steps of filtering, framing, and focusing on specific aspects, the measures used in various semantic domains negotiate distinct trade-offs between abstraction and specialization. As a consequence, the transparent communication of such measures must explicate the perspectives encapsulated in their derivation. To demonstrate the explanatory scope of our model, we use it to clarify theoretical debates on biases and facilitation effects in Bayesian reasoning and to integrate the scientific measures from various semantic domains within a unifying framework. A better understanding of problem structures, representational transparency, and the role of perspectives in the scientific process yields both theoretical insights and practical applications.
The echo in flu-vaccination echo chambers : Selective attention trumps social influence
2020-02, Giese, Helge, Neth, Hansjörg, Moussaïd, Mehdi, Betsch, Cornelia, Gaissmaier, Wolfgang
Online discussions may impact the willingness to get vaccinated. This experiment tests how groups of individuals with consistent and inconsistent attitudes towards flu vaccination attend to and convey information online, and how they alter their corresponding risk perceptions.
Out of 1859 MTurkers, we pre-selected 208 people with negative and 221 people with positive attitudes towards flu vaccinations into homogeneous or heterogeneous 3-link experimental diffusion chains. We assessed (i) which information about flu vaccinations participants conveyed to the subsequent link, (ii) how flu-vaccination related perceptions were altered by incoming messages, and (iii) how participants perceived incoming information.
Participants (i) selectively conveyed attitude-consistent information, but exhibited no overall anti-vaccination bias, (ii) were reluctant to alter their flu-vaccination related perceptions in response to messages, and (iii) evaluated incoming information consistent with their prior attitudes as more convincing.
Flu-vaccination related perceptions are resilient against contradictions and bias online communication. Contrary to expectations, there was no sign of amplification of anti-vaccine attitudes by online communication.
FFTrees : A toolbox to create, visualize, and evaluate fast-and-frugal decision trees
2017, Phillips, Nathaniel D., Neth, Hansjörg, Woike, Jan K., Gaissmaier, Wolfgang
Fast-and-frugal trees (FFTs) are simple algorithms that facilitate efficient and accurate decisions based on limited information. But despite their successful use in many applied domains, there is no widely available toolbox that allows anyone to easily create, visualize, and evaluate FFTs. We fill this gap by introducing the R package FFTrees. In this paper, we explain how FFTs work, introduce a new class of algorithms called fan for constructing FFTs, and provide a tutorial for using the FFTrees package. We then conduct a simulation across ten real-world datasets to test how well FFTs created by FFTrees can predict data. Simulation results show that FFTs created by FFTrees can predict data as well as popular classification algorithms such as regression and random forests, while remaining simple enough for anyone to understand and use.