Evidence map›Paper›PMID 39167472›Full record

ArticleHealth policy and planning2024

Gender-responsive monitoring and evaluation for health systems.

Rosemary Morgan, Anna Kalbarczyk, Michele Decker, Shatha Elnakib, Tak Igusa, Amy Luo, Ayoyemi Toheeb Oladimeji, Milly Nakatabira, David H Peters, Indira Prihartono and 1 more

Erratum issuedAbstract read
In one paragraph

Article in Health policy and planning, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

11 authors.

Rosemary MorganDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.ORCID 0000-0001-5009-8470
Anna KalbarczykDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.ORCID 0000-0002-6143-8634
Michele DeckerDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.
Shatha ElnakibDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.
Tak IgusaDepartment of Civil and Systems Engineering, Johns Hopkins Whiting School of Engineering, 3400 N Charles St, Baltimore, MD 21218, United States.
Amy LuoDepartment of Population, Family and Reproductive Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.
Ayoyemi Toheeb OladimejiDepartment of Civil and Systems Engineering, Johns Hopkins Whiting School of Engineering, 3400 N Charles St, Baltimore, MD 21218, United States.
Milly NakatabiraDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.
David H PetersFaculty of Health, York University, 4700 Keele St, Toronto, Ontario M3J 1P3, Canada.
Indira PrihartonoDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.
Anju MalhotraDepartment of International Health, Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD 21205, United States.

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
Gates Foundation INV032701NIMH NIH HHS T32 MH122357
6 · The paper itself

Abstract

Gender-responsive monitoring and evaluation (M&E) for health and health systems interventions and programs is vital to improve health, health systems, and gender equality outcomes. It can be used to identify and address gender disparities in program participation, outcomes and benefits, as well as ensure that programs are designed and implemented in a way that is inclusive and accessible for all. While gender-responsive M&E is most effective when interventions and programs intentionally integrate a gender lens, it is relevant for all health systems programs and interventions. Within the literature, gender-responsive M&E is defined in different and diverse ways, making it difficult to operationalize. This is compounded by the complexity and multi-faceted nature of gender. Within this methodological musing, we present our evolving approach to gender-responsive M&E which we are operationalizing within the Monitoring for Gender and Equity project. We define gender-responsive M&E as intentionally integrating the needs, rights, preferences of, and power relations among, women and girls, men and boys, and gender minority individuals, as well as across social, political, economic, and health systems in M&E processes. This is done through the integration of different types of gender data and indicators, including: sex- or gender-specific, sex- or gender-disaggregated, sex- or gender-specific/disaggregated which incorporate needs, rights and preferences, and gender power relations and systems indicators. Examples of each of these are included within the paper. Active approaches can also enhance the gender-responsiveness of any M&E activities, including incorporating an intersectional lens and tailoring the types of data and indicators included and processes used to the specific context. Incorporating gender into the programmatic cycle, including M&E, can lead to more fit-for-purpose, effective and equitable programs and interventions. The framework presented in this paper provides an outline of how to do this, enabling the uptake of gender-responsive M&E.

Indexed as

Delivery of Health CareFemaleGender EquityHumansMaleProgram EvaluationSex FactorsequityGendergender equityhealth inequalitieshealth systemsmonitoring and evaluation

Identifiers

PMID39167472
PMCPMC11474598

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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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.