探索如何提高波兰和南亚社区在大数据研究方面的参与. 使用COM-B模型进行定性研究
Piotr Teodorowski1, Sarah E Rodgers1, Kate Fleming2
1Department of Public Health, Policy & Systems, University of Liverpool.
International journal of population data science
|September 6, 2023
概括
这项研究探讨了如何在英国的南亚和波兰社区中增加公众参与大数据研究. 研究结果表明,使用COM-B模型可以帮助研究人员有效地参与很少听到的群体.
科学领域:
- 卫生研究 卫生研究 卫生研究
- 大数据的大数据大数据
- 公众参与 公众参与
背景情况:
- 公众参与研究确保研究以人为中心和相关.
- 参与多元化社区对于包容性研究至关重要.
- 有限的证据表明,很少听到的社区参与大数据研究.
研究的目的:
- 了解如何鼓励英国的南亚和波兰社区参与大数据研究的公众参与计划.
- 确定影响公众愿意为大数据研究作出贡献的因素.
主要方法:
- 对英国的波兰人和南亚参与者进行了40次Zoom采访.
- 参与者之前没有作为公共贡献者的经验.
- 使用反射主题分析分析了采访成绩单.
主要成果:
- 确定了八个主题,包括参与者对数据再利用的看法.
- 将主题映射到能力-机会-动机-行为 (COM-B) 模型中.
- 发现了多个因素影响成为公共贡献者的意愿.
结论:
- 这项研究是第一个使用COM-B模型来加强罕见的社区参与大数据研究的研究.
- 结果可以指导研究人员识别对公众参与的影响.
- 该COM-B模型为制定有针对性的参与策略提供了一个框架.
更多相关视频
08:53Integrating Computerized Linguistic and Social Network Analyses to Capture Addiction Recovery Capital in an Online Community
Published on: May 31, 2019
5.2K
13:40Combining Computer Game-Based Behavioural Experiments With High-Density EEG and Infrared Gaze Tracking
Published on: December 16, 2010
16.8K
相关概念视频
Ethnic Identity within a Larger Culture
59
Adolescents from ethnic minority backgrounds face a multifaceted journey in forming their identities, shaped by the intersections of cultural expectations and personal exploration. For these adolescents, identity formation involves not only typical developmental challenges but also navigating the perceptions and attitudes of the majority culture. As they grow, adolescents in ethnic minority groups often become increasingly aware of stereotypes, social biases, and discrimination, all of which...
59
Stereotype Content Model
14.8K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.8K
Typical Model Studies
380
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
380
Observational Studies
8.7K
Observational studies are a type of analytical study where researchers observe events without any interventions. In other words, the researcher does not influence the response variable or the experiment's outcome.
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
There are three types of observational studies – Prospective, retrospective, and cross-sectional.
Prospective Study
Prospective studies, also known as longitudinal or cohort studies, are carried out by collecting future data from groups sharing similar characteristics. One...
8.7K
Community Based Intervention
65
Community-based interventions in mental health represent a paradigm shift from institution-centered care to treatments embedded within the fabric of local communities. By prioritizing inclusion and leveraging existing societal structures, this approach fosters a supportive environment conducive to addressing mental health challenges while promoting individual dignity and agency.
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
Foundations of Community Mental Health Programs
Central to the success of community-based interventions is the...
65
Statistical Methods for Analyzing Epidemiological Data
408
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
408
