49 research outputs found

    Recruiting participants for interventions to prevent the onset of depressive disorders: Possibile ways to increase participation rates

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    Background: Although indicated prevention of depression is available for about 80% of the Dutch population at little or no cost, only a small proportion of those with subthreshold depression make use of these services. Methods: A narrative review is conducted of the Dutch preventive services in mental health care, also addressing the problem of low participation rates. We describe possible causes of these low participation rates, which may be related to the participants themselves, the service system, and the communication to the public, and we put forward possible solutions to this problem. Results: There are three main groups of reasons why the participation rates are low: reasons within the participants (e.g., not considering themselves as being at risk; thinking the interventions are not effective; or being unwilling to participate because of the stigma associated with depression); reasons within the health care system; and reasons associated with the communication about the preventive services. Possible solutions to increasing the participation rate include organizing mass media campaigns, developing internet-based preventive interventions, adapting preventive interventions to the needs of specific subpopulations, positioning the services in primary care, integrating the interventions in community-wide interventions, and systematically screening high-risk groups for potential participants. Discussion: Prevention could play an important role in public mental health in reducing the enormous burden of depression. However, before this can be realized more research is needed to explore why participation rates are low and how these rates can be improved

    A View from the Top: International Politics, Norms and the Worldwide Growth of NGOs

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    This article provides a top-down explanation for the rapid growth of nongovernmental organizations (NGOs) in the postwar period, focusing on two aspects of political globalization. First, I argue that international political opportunities in the form of funding and political access have expanded enormously in the postwar period and provided a structural environment highly conducive to NGO growth. Secondly, I present a norm-based argument and trace the rise of a pro-NGO norm in the 1980s and 1990s among donor states and intergovernmental organizations (IGOs), which has actively promoted the spread of NGOs to non-Western countries. The article ends with a brief discussion of the symbiotic relationship among NGOs, IGOs, and states promoting international cooperation

    National identity predicts public health support during a global pandemic

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    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 the early stage of the COVID-19 pandemic (April-May 2020). Respondents who reported identifying more strongly with their nation consistently reported greater engagement in public health behaviours and support for public health policies. Results were similar for representative and non-representative national samples. Study 2 (N = 42 countries) conceptually replicated the central finding using aggregate indices of national identity (obtained using the World Values Survey) and a measure of actual behaviour change during the pandemic (obtained from Google mobility reports). Higher levels of national identification prior to the pandemic predicted lower mobility during the early stage of the pandemic (r = −0.40). We discuss the potential implications of links between national identity, leadership, and public health for managing COVID-19 and future pandemics.publishedVersio

    Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

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    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 multinational data collected by the International Collaboration on the Social and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar results were found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, and collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-neglible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic.Peer reviewe

    National identity predicts public health support during a global pandemic (vol 13, 517, 2022) : National identity predicts public health support during a global pandemic (Nature Communications, (2022), 13, 1, (517), 10.1038/s41467-021-27668-9)

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    Publisher Copyright: © The Author(s) 2022.In this article the author name ‘Agustin Ibanez’ was incorrectly written as ‘Augustin Ibanez’. The original article has been corrected.Peer reviewe

    Predicting attitudinal and behavioral responses to COVID-19 pandemic using machine learning

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    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 and Moral Psychology of COVID-19 (N = 51,404) to test the predictive efficacy of constructs from social, moral, cognitive, and personality psychology, as well as socio-demographic factors, in the attitudinal and behavioral responses to the pandemic. The results point to several valuable insights. Internalized moral identity provided the most consistent predictive contribution—individuals perceiving moral traits as central to their self-concept reported higher adherence to preventive measures. Similar was found for morality as cooperation, symbolized moral identity, self-control, open-mindedness, collective narcissism, while the inverse relationship was evident for the endorsement of conspiracy theories. However, we also found a non-negligible variability in the explained variance and predictive contributions with respect to macro-level factors such as the pandemic stage or cultural region. Overall, the results underscore the importance of morality-related and contextual factors in understanding adherence to public health recommendations during the pandemic
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