Related Experiment Video
Updated: Dec 9, 2025
06:52
Assessment of Dependence in Activities of Daily Living Among Older Patients in an Acute Care Unit
Published on: September 30, 2020
10.3K
Age Differences in Work-Disability Duration Across Canada: Examining Variations by Follow-Up Time and Context
Jonathan K Fan1,2, Robert A Macpherson3, Peter M Smith4,5,6
1Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada. jon.fan@mail.utoronto.ca.
Journal of Occupational Rehabilitation
|September 10, 2020
Summary
Older workers are less likely to transition off wage-replacement benefits initially after injury. However, age-related differences in disability duration diminish over time, suggesting age is not always a strong predictor of worse outcomes.
Area of Science:
- Occupational health
- Epidemiology
- Biostatistics
Background:
- Understanding age-related differences in disability duration is crucial for effective workers' compensation policies.
- Previous research often shows older workers experience longer recovery periods, but nuances across follow-up times require investigation.
Purpose of the Study:
- To analyze age-specific differences in wage-replacement benefit duration following workplace injuries.
- To examine how these age-related differences evolve over different follow-up periods.
Main Methods:
- Utilized administrative claims data from six Canadian workers' compensation systems (2011-2015).
- Included 751,679 time-loss claims for workers aged 15-80 years with work-related injuries/illnesses.
- Employed survival analysis with relaxed proportionality constraints to assess age-related hazards of transitioning off benefits.
Main Results:
- Older age groups demonstrated a lower likelihood of transitioning off wage-replacement benefits compared to younger groups (e.g., 55-64 vs. 15-24 years: HR 0.62).
- Significant age-related differences in hazard rates were observed, particularly at earlier follow-up times.
- These absolute and relative differences attenuated over longer follow-up periods, approaching a null effect.
Conclusions:
- Older age is not consistently associated with prolonged disability duration outcomes in workers' compensation claims.
- Findings highlight the dynamic nature of recovery and the importance of considering follow-up time in age-related analyses.
- The use of multi-jurisdictional data enhances the external validity of these insights into workplace injury recovery processes.
More Related Videos
Related Concept Videos
02:20Longitudinal Research
12.9K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
12.9K
01:15Assumptions of Survival Analysis
295
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
295
01:26Longitudinal Studies
373
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...
373
01:20Comparing the Survival Analysis of Two or More Groups
461
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...
461
01:20Actuarial Approach
218
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
218
01:18Introduction To Survival Analysis
569
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
569