Recently Added
CLEAR searches the existing literature for research relevant to this topic area's focus. Browse the most recently reviewed research below.
Displaying 161 - 170 of 170
Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of a work flexibility intervention called STAR (Support. Transform. Achieve. Results) on workers’ expectations of retirement age and bridge jobs. The…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of the national health policies of the United States and Denmark on employment of older workers after a health shock, defined as a new cancer or…Study Type: Causal Impact Analysis
The study examined the impact of removing the Social Security earnings test on Social Security claims, earnings, and labor force participation for female beneficiaries. The study used a statistical…Study Type: Causal Impact Analysis
The study examined the impact of pension reform under the California State Teachers’ Retirement System (CalSTRS) on retirement timing. The author used a statistical model and data from retirement-…Study Type: Causal Impact Analysis
The study examined the impact of uncapping mandatory retirement on retirement ages at postsecondary institutions The study used a statistical model to examine the age of retirement before and after…Study Type: Causal Impact Analysis
The study examined the impact of Individual Placement and Support (IPS) on competitive employment for older people with schizophrenia The study was a randomized controlled trial (RCT) conducted at a…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of flexibility in hours of work on the likelihood that older workers separate from an employer. The study used a statistical model to compare the job…Study Type: Causal Impact Analysis
The study objective is to examine the impact of the Personal Responsibility and Work Opportunity Reconciliation Act (PRWORA) of 1996 on employment outcomes of foreign-born people and noncitizens…Study Type: Causal Impact Analysis
The study examined the impact of Individual Placement and Support (IPS) on competitive employment for older people with schizophrenia The study was a randomized controlled trial (RCT) and used…Study Type: Causal Impact Analysis
The study’s objective was to examine the impact of Medicare as a Secondary Payer (MSP) on older workers’ labor force participation and full-time employment The study used a nonexperimental…
CLEAR Icon Key
Below is a key for icons used to indicate important details about a study, such as its type, evidence rating, and outcome findings.
High Causal Evidence
Strong evidence the effects are caused by the examined intervention.
Moderate Causal Evidence
Evidence that the effects are caused to some degree by the examined intervention.
Low Causal Evidence
Little evidence that the effects are caused by the examined intervention.
Causal Impact Analysis
Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
Descriptive Analysis
Describes a program, policy, or intervention using qualitative or quantitative methods.
Implementation Analysis
Examines the implementation of a program, policy, or intervention.
Favorable
The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
Mixed
The study found some favorable and some unfavorable impacts in the outcome domain.
None
The study found no statistically significant impacts in the outcome domain.
Unfavorable
The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
Not applicable
Not applicable because no outcomes were examined in the outcome domain.
Favorable - low evidence
The study found at least one favorable impact in the outcome domain, and no unfavorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Mixed - low evidence
The study found some favorable and some unfavorable impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
None - low evidence
The study found no statistically significant impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Unfavorable - low evidence
The study found at least one unfavorable impact in the outcome domain, and no favorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
