Evidence map›Paper›PMID 41767595›Full record

ArticleSSM - health systems2025

Towards a common understanding of gender-responsive monitoring and evaluation for health programs and interventions: Evidence from a scoping review.

Anna Kalbarczyk, Daniel Krugman, Shatha Elnakib, Elizabeth Hazel, Amy Luo, Anju Malhotra, Rosemary Morgan

Abstract read
In one paragraph

Article in SSM - health systems, 2025. 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

7 authors.

Anna KalbarczykDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-6143-8634
Daniel KrugmanDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-2350-5357
Shatha ElnakibDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0003-2316-4211
Elizabeth HazelDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-9176-3278
Amy LuoDepartment of Population, Family, and Reproductive Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0002-4466-375X
Anju MalhotraDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-9653-2754
Rosemary MorganDepartment of International Health, Bloomberg School of Public Health, Baltimore, MD, USA.ORCID 0000-0001-5009-8470

Funding

Integrating data for causal inference in behavioral healthT32MH122357 · NIMH · JOHNS HOPKINS UNIVERSITY · PI Rashelle Jean Musci, Elizabeth A. Stuart · 2020 to 2026
$1.8M
Bill & Melinda Gates Foundation INV-032701NIMH NIH HHS T32 MH122357
6 · The paper itself

Abstract

Given the many approaches to and definitions of gender responsive monitoring and evaluation (M&E) for health programs and interventions there is a lack of clarity on how to operationalize it including what to measure and how to measure it. We conducted a scoping review to understand what makes M&E gender responsive. We included 31 studies and conducted two rounds of extraction to delineate ways in which gender was integrated into M&E. Twelve articles described the use of theory to guide M&E though most were not related to gender. Twelve articles employed a gender score in data collection, most of which measured Likert scale responses related to gender equity. Even though most studies did not use a specific gender framework, most incorporated gender domains in their analysis. Seven studies used participatory methods in the design and implementation of M&E. Most studies conducted M&E on programs or interventions that were designed to be gender intentional and related to gender issues. Gender responsive M&E intentionally integrates gender into the M&E process, regardless of how gender-intentional the program or intervention is. Gender dimensions can be identified through gender theories, models, scores, and frameworks to inform tool development, data collection, analysis, and stakeholder engagement processes.

Indexed as

GenderHealth outcomesMonitoring and evaluationRMNCAHN

Identifiers

PMID41767595
PMCPMC12945375

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.