Evidence map›Paper›PMID 33898730›Full record

ArticleSSM - population health2021

Powering population health research: Considerations for plausible and actionable effect sizes.

Ellicott C Matthay, Erin Hagan, Laura M Gottlieb, May Lynn Tan, David Vlahov, Nancy Adler, M Maria Glymour

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in SSM - population health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed, 7 pooled it
–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

88 citing papers in PubMed, 7 syntheses or guidelines pooled it.

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  12. Testing the Efficacy of a Culturally Adapted Family Dementia Caregiver Intervention (REACH VN): Results From a Cluster Randomized Controlled Trial in Northern Vietnam.The American journal of geriatric psychiatry : official journal of the American Association for Geriatric Psychiatry · 2025
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28 more citing papers are in PubMed but not listed here.

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

7 authors.

Ellicott C MatthayCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.
Erin HaganCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.
Laura M GottliebCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.
May Lynn TanCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.
David VlahovYale School of Nursing at Yale University, 400 West Campus Drive, Room 32306, Orange, CT, 06477, USA.
Nancy AdlerCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.
M Maria GlymourCenter for Health and Community, University of California, San Francisco, 3333 California St., Suite 465, Campus Box 0844, San Francisco, CA, 94143-0844, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Evidence for Action (E4A), a signature program of the Robert Wood Johnson Foundation, funds investigator-initiated research on the impacts of social programs and policies on population health and health inequities. Across thousands of letters of intent and full proposals E4A has received since 2015, one of the most common methodological challenges faced by applicants is selecting realistic effect sizes to inform calculations of power, sample size, and minimum detectable effect (MDE). E4A prioritizes health studies that are both (1) adequately powered to detect effect sizes that may reasonably be expected for the given intervention and (2) likely to achieve intervention effects sizes that, if demonstrated, correspond to actionable evidence for population health stakeholders. However, little guidance exists to inform the selection of effect sizes for population health research proposals. We draw on examples of five rigorously evaluated population health interventions. These examples illustrate considerations for selecting realistic and actionable effect sizes as inputs to calculations of power, sample size and MDE for research proposals to study population health interventions. We show that plausible effects sizes for population health interventions may be smaller than commonly cited guidelines suggest. Effect sizes achieved with population health interventions depend on the characteristics of the intervention, the target population, and the outcomes studied. Population health impact depends on the proportion of the population receiving the intervention. When adequately powered, even studies of interventions with small effect sizes can offer valuable evidence to inform population health if such interventions can be implemented broadly. Demonstrating the effectiveness of such interventions, however, requires large sample sizes.

Indexed as

Effect sizeHealth equityPopulation healthSample sizeSocial interventionStatistical power

Identifiers

PMID33898730
PMCPMC8059081

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.