在加拿大的COVID-19大流行之前和期间,娱乐屏幕时间的社会人口统计差异
Stephanie Toigo1, Marisol T Betancourt1, Stephanie A Prince1,2
1Centre for Surveillance and Applied Research, Public Health Agency of Canada.
Health reports
|May 17, 2024
概括
在COVID-19大流行期间,娱乐屏幕时间增加了,较少的加拿大人符合移动指南. 某些社会人口统计学群体更有可能满足建议,突出需要有针对性的干预措施.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 行为科学 行为科学
背景情况:
- 娱乐性屏幕时间在全球范围内不断增加.
- COVID-19 流行病加剧了加拿大青年和成年人的这种趋势.
- 增加屏幕时间与自我报告的心理健康结果较差相关.
研究的目的:
- 为了比较在加拿大COVID-19大流行之前和期间满足娱乐屏幕时间建议的流行率.
- 确定与会议屏幕时间建议相关的社会人口统计因素.
- 为流行病恢复的公共卫生战略提供信息.
主要方法:
- 利用了2017年,2018年和2021年加拿大社区健康调查的数据.
- 采用后勤回归来分析社会人口统计学特征和会议屏幕时间建议之间的关联.
- 疫情前和期间的屏幕时间流行的比较.
主要成果:
- 与之前相比,在大流行期间,较少的加拿大人满足了娱乐屏幕时间建议.
- 在大多数社会人口统计学群体中,满足建议的流行率下降.
- 某些特定群体,包括女性,农村居民,南亚人,移民和医疗保健工作者,在疫情期间更有可能满足建议.
结论:
- 随着COVID-19大流行,加拿大大众对娱乐性屏幕时间指南的遵守率下降.
- 确定那些对增加屏幕时间更有弹性的特定社会人口群体至关重要.
- 需要持续监测和量身定制的干预措施,以解决大流行对屏幕时间行为的长期影响.
相关概念视频
01:50Cross-Sectional Research
11.3K
In cross-sectional research, a researcher compares multiple segments of the population at the same time. If they were interested in people's dietary habits, the researcher might directly compare different groups of people by age. Instead of following a group of people for 20 years to see how their dietary habits changed from decade to decade, the researcher would study a group of 20-year-old individuals and compare them to a group of 30-year-old individuals and a group of 40-year-old...
11.3K
01:08Prevalence and Incidence
466
In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
466
01:29Bias in Epidemiological Studies
251
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
251