David Schultner
Biographic Data
| ID | 1980311 |
|---|---|
| NAME | David Schultner |
| GIVEN NAMES | David |
| FAMILY NAME | Schultner |
| SIGNATURE | SCHULTNER D |
| AFFILIATIONS | Karolinska Institutet |
| ORCID | 0000-0003-2253-4065 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Feature-based reward learning shapes human social learning strategies
Human adaptation depends on individuals strategically choosing whom to learn from. A mosaic of social learning strategies-such as copying majorities or successful others-has been identified. Influential theories conceive of these strategies as fixed heuristics, independent of experience. However, such accounts cannot explain the flexibility and individual variability prevalent in social learning. Here we advance a domain-general reward learning f…
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
No prominent works on this page.
National identity predicts public health support during a global pandemic
Changing collective behaviour and supporting non-pharmaceutical interventions is an important component in mitigating virus transmission during a pandemic. In a large international collaboration (Study 1, N = 49,968 across 67 countries), we investigated self-reported factors associated with public health behaviours (e.g., spatial distancing and stricter hygiene) and endorsed public policy interventions (e.g., closing bars and restaurants) during …
Predicting attitudinal and behavioral responses to Covid-19 pandemic using machine learning
At the beginning of 2020, COVID-19 became a global problem. Despite all the efforts to emphasize the relevance of preventive measures, not everyone adhered to them. Thus, learning more about the characteristics determining attitudinal and behavioral responses to the pandemic is crucial to improving future interventions. In this study, we applied machine learning on the multi-national data collected by the International Collaboration on the Social…
Feature-based reward learning shapes human social learning strategies
Human adaptation depends on individuals strategically choosing whom to learn from. A mosaic of social learning strategies-such as copying majorities or successful others-has been identified. Influential theories conceive of these strategies as fixed heuristics, independent of experience. However, such accounts cannot explain the flexibility and individual variability prevalent in social learning. Here we advance a domain-general reward learning f…
Computer Science (3 works) · 2019-20 coronavirus outbreak (2 works) · Artificial Intelligence (2 works) · Cognitive psychology (2 works) · COVID-19 and Mental Health (2 works) · COVID-19 epidemiological studies (2 works) · Medicine (2 works) · Pandemic (2 works) · Psychology (2 works) · Cognitive science (1 works)