以前的病假是否会影响职业劳动力市场培训后的工作参与? 一个差异差异倾向得分匹配方法
Laura Salonen1, Svetlana Solovieva1, Antti Kauhanen2
1Finnish Institute of Occupational Health, Helsinki, Finland.
European journal of public health
|August 27, 2023
概括
有病假 (SA) 史的求职者从劳动力市场培训 (LMT) 中获得的益处较小. 这种影响在女性和患有精神疾病的人群中更为明显,突出显示了对定制就业支持的需求.
科学领域:
- 社会科学 社会科学 社会科学
- 经济学 经济学 经济学
- 公共卫生 公共卫生
背景情况:
- 减少工作能力对求职者来说是一个重要的障碍,影响了他们长期的劳动力市场依恋.
- 积极的劳动力市场计划,特别是职业劳动力市场培训 (LMT),是提高就业能力的常见策略.
- 在有工作残疾史,如病假 (SA) 的个人中,LMT的有效性需要进一步调查.
研究的目的:
- 检查LMT对SA史和没有SA史的求职者在工作参与度上的差异影响.
- 根据SA史,性别和就业背景,确定影响LMT有效性的因素.
主要方法:
- 利用芬兰国家登记处的数据,从16 062名LMT参与者 (2008-2015) 年龄在25-59岁之间获取数据.
- 雇员倾向性得分匹配,以比较具有和没有SA史的参与者,控制社会人口统计学和与工作有关的因素.
- 应用差异分析来评估LMT前后劳动参与的变化.
主要成果:
- 与没有SA的个人相比,具有SA史的人在LMT后的工作参与率的增加较小.
- 这种差异的幅度因性别和就业历史而异,在LMT后1-3年,女性比男性 (3.9-6.2个百分点) 经历了更大的差异 (2.0-4.3个百分点).
- 当SA因精神障碍而导致时,SA史对LMT有效性的负面影响更为明显.
结论:
- 工作残疾的历史,特别是由于心理健康问题,可以阻碍LMT在改善工作参与方面的好处.
- 为求职者提供增强就业的措施应考虑并解决有工作残疾史的个人所面临的挑战.
- 量身定制的干预措施对于优化各种求职人口的LMT结果至关重要.
更多相关视频
07:31A Computerized Functional Skills Assessment and Training Program Targeting Technology Based Everyday Functional Skills
Published on: February 13, 2020
7.0K
07:01Working Memory Training for Older Participants: A Control Group Training Regimen and Initial Intellectual Functioning Assessment
Published on: September 20, 2020
4.8K
相关概念视频
Comparing the Survival Analysis of Two or More Groups
222
Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
222
Wilcoxon Signed-Ranks Test for Matched Pairs
160
The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
160
Factors Affecting Illness
4.3K
When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
For instance, risk factors are connected to illness,...
4.3K
Odds Ratio
163
The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
163
Sign Test for Matched Pairs
159
The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
To conduct the sign test, we first calculate the differences in...
To conduct the sign test, we first calculate the differences in...
159
Longitudinal Studies
187
Longitudinal studies are also widely used in other medical and social science fields. For instance, in cardiovascular research, they can monitor patients' health over decades to identify risk factors for heart disease, such as high cholesterol or smoking, and evaluate the long-term effectiveness of preventive measures. Similarly, in mental health studies, researchers might follow individuals from adolescence into adulthood to understand the development and progression of conditions like...
187
