Evidence map›Paper›PMID 39434785›Full record

ArticleHealth affairs scholar2024

Learning from employer experiences with paid leave policy expansions during the COVID-19 pandemic.

William H Dow, Julia M Goodman, Paloma Lin, Paige Park

Abstract read
In one paragraph

Article in Health affairs scholar, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

William H DowSchool of Public Health, University of California-Berkeley, Berkeley, CA 94720, USA.ORCID https://orcid.org/0000-0002-4080-1668
Julia M GoodmanOHSU-PSU School of Public Health, Portland, OR 97201, USA.ORCID https://orcid.org/0000-0002-9296-8697
Paloma LinSchool of Public and International Affairs, Princeton University, Princeton, NJ 08540, USA.ORCID https://orcid.org/0009-0005-9180-9300
Paige ParkSchool of Public Health, University of California-Berkeley, Berkeley, CA 94720, USA.ORCID https://orcid.org/0000-0001-5930-6758

Funding

INTERDISCIPLINARY TRAINING IN DEMOGRAPHYT32HD007275 · NICHD · UNIVERSITY OF CALIFORNIA BERKELEY · PI FEEHAN, DENNIS MICHAEL · 1985 to 2025
$5.3M
NICHD NIH HHS T32 HD007275
6 · The paper itself

Abstract

The United States does not have a federal policy offering employees paid leave. We study employer attitudes toward the Families First Coronavirus Response Act (FFCRA) federal emergency paid leave policies temporarily adopted during the COVID-19 pandemic to draw lessons for proposed permanent federal paid leave policies. We analyzed a 2021 survey of 300 San Francisco Bay Area employers to examine employers' experiences with paid sick leave (PSL) and paid family leave (PFL) policies during the COVID-19 pandemic, along with their attitudes regarding FFCRA paid leave. Most firms reported that it was not difficult to comply with or seek reimbursement for FFCRA leave. Nevertheless, most smaller firms did report difficulty in understanding policy details, and many reported being unaware of FFCRA paid leave availability. FFCRA paid leave was broadly popular among firms aware of it: 64% supported (9% opposed) the PSL provisions, and 52% supported (12% opposed) PFL. However, support for permanent extension dropped to just over 40%, despite this Bay Area sample having long familiarity with California's state paid leave policies. We conclude that federal pandemic paid leave offers a potential model that could be refined for future paid leave policies, but support is mixed.

Indexed as

COVID-19family leavepublic policysick leave

Identifiers

PMID39434785
PMCPMC11493094

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.