Refine
Has Fulltext
- yes (4)
Is part of the Bibliography
- yes (4)
Document Type
- Journal article (4)
Language
- English (4)
Keywords
- Argentina (1)
- Latin America (1)
- Venezuela (1)
- break-in parties (1)
- data collection (1)
- democracy (1)
- digital phenotyping (1)
- ecological momentary assessment (1)
- end-user programming (1)
- informality (1)
- longitudinal studies (1)
- mental effort (1)
- mobile crowdsensing (1)
- mobile health (1)
- neighborhood movement (1)
- piquetero movement (1)
- smart mobile devices (1)
- social movements (1)
- social self‐organization (1)
- state–society relations (1)
- types of government (1)
- usability study (1)
Institute
- Institut für Politikwissenschaft und Soziologie (2)
- Institut für Hygiene und Mikrobiologie (1)
- Institut für Klinische Epidemiologie und Biometrie (1)
- Klinik und Poliklinik für Anästhesiologie (ab 2004) (1)
- Klinik und Poliklinik für Kinder- und Jugendpsychiatrie, Psychosomatik und Psychotherapie (1)
- Klinik und Poliklinik für Psychiatrie, Psychosomatik und Psychotherapie (1)
- Medizinische Klinik und Poliklinik I (1)
Physical and mental well-being during the COVID-19 pandemic is typically assessed via surveys, which might make it difficult to conduct longitudinal studies and might lead to data suffering from recall bias. Ecological momentary assessment (EMA) driven smartphone apps can help alleviate such issues, allowing for in situ recordings. Implementing such an app is not trivial, necessitates strict regulatory and legal requirements, and requires short development cycles to appropriately react to abrupt changes in the pandemic. Based on an existing app framework, we developed Corona Health, an app that serves as a platform for deploying questionnaire-based studies in combination with recordings of mobile sensors. In this paper, we present the technical details of Corona Health and provide first insights into the collected data. Through collaborative efforts from experts from public health, medicine, psychology, and computer science, we released Corona Health publicly on Google Play and the Apple App Store (in July 2020) in eight languages and attracted 7290 installations so far. Currently, five studies related to physical and mental well-being are deployed and 17,241 questionnaires have been filled out. Corona Health proves to be a viable tool for conducting research related to the COVID-19 pandemic and can serve as a blueprint for future EMA-based studies. The data we collected will substantially improve our knowledge on mental and physical health states, traits and trajectories as well as its risk and protective factors over the course of the COVID-19 pandemic and its diverse prevention measures.
Although Lijphart's typology of consensus and majoritarian democracy can be regarded as the most widely used tool to classify democratic regimes, it has been rarely applied to Latin America so far. We try to fill this gap by adapting Lijphart's typological framework to the Latin American context in the following way. In contrast to previous studies, we treat the type of democracy as an independent variable and include informal factors such as clientelism or informal employment in our assessment of democratic patterns. On this basis, we aim to answer the following questions. First, how did the patterns of democracy evolve in Latin America over the two decades between 1990 and 2010 and what kind of differences can be observed in the region? Second, what are the institutional determinants of the observed changes? We focus on the emergence of new parties because of their strong impact on the first dimension of Lijphart's typology. From our observations we draw the following tentative conclusions: If strong new parties established themselves in the party system but failed to gain the presidency, they pushed the system towards consensualism. Conversely, new parties that gained the presidency produced more majoritarian traits.
To deal with drawbacks of paper-based data collection procedures, the QuestionSys approach empowers researchers with none or little programming knowledge to flexibly configure mobile data collection applications on demand. The mobile application approach of QuestionSys mainly pursues the goal to mitigate existing drawbacks of paper-based collection procedures in mHealth scenarios. Importantly, researchers shall be enabled to gather data in an efficient way. To evaluate the applicability of QuestionSys, several studies have been carried out to measure the efforts when using the framework in practice. In this work, the results of a study that investigated psychological insights on the required mental effort to configure the mobile applications are presented. Specifically, the mental effort for creating data collection instruments is validated in a study with N=80 participants across two sessions. Thereby, participants were categorized into novices and experts based on prior knowledge on process modeling, which is a fundamental pillar of the developed approach. Each participant modeled 10 instruments during the course of the study, while concurrently several performance measures are assessed (e.g., time needed or errors). The results of these measures are then compared to the self-reported mental effort with respect to the tasks that had to be modeled. On one hand, the obtained results reveal a strong correlation between mental effort and performance measures. On the other, the self-reported mental effort decreased significantly over the course of the study, and therefore had a positive impact on measured performance metrics. Altogether, this study indicates that novices with no prior knowledge gain enough experience over the short amount of time to successfully model data collection instruments on their own. Therefore, QuestionSys is a helpful instrument to properly deal with large-scale data collection scenarios like clinical trials.
Exploring the Relationship Between Social Movement Organizations and the State in Latin America
(2023)
Under conditions of weak statehood, societal actors are supposed to assume functions usually attributed to the state. Social self-organization is expected to emerge when the state leaves important social problems unattended. Should social self-organization, therefore, be regarded as a reaction to state weakness and as compensation for state failure in the provision of basic services? Does society organize itself on its own in areas where the state is absent or ineffective? By the example of two Latin American social movements, this article aims to show that social self-organization—at least on a larger scale—is not independent of the state, but rather a result of a dynamic interaction with the state. The two examples this article explores are the middle-class Venezuelan neighborhood movement and the Argentine piquetero movement of unemployed workers. Both movements emerged as reactions to the state’s failure and retreat from essential social functions and both developed into extensive and influential social actors. For that reason, they can be regarded as crucial cases for observing the patterns and conditions of social self-organization and autonomous collective action within the specific Latin American context. Despite their different backgrounds and social bases, the two cases reveal remarkable similarities. They show that the emergence and development of self-organized social groups cannot be conceived simply as a reaction to state weakness, but rather should be viewed as a dynamic interaction with the state.