Evidence-based Measures of Empowerment for Research on Gender Equality

Photograph by Prashant Panjiar © Bill & Melinda Gates Foundation


To identify the best measure for your study, we recommend that you consider three core factors:  (1) measure “specs”, (2) population demographics, and (3) research constraints. Measure “specs” or specifics broadly deals with the nature, availability, and rigor of measures used to quantify a given construct; based on “what” the measure is and how useful of a tool it is purported to be according to the literature and study needs. Population demographics deals with attributes of the population of interest or target population to “whom” the measure will be administered to. Research constraints deals with aspects such as time, funding, and situational or personnel details that one considers when thinking about “how” the measure will be administered. Below we highlight some on the aspects subsumed under each factor to help you determine the “best” measure. Additional information on determining the ideal measure for use can be found in our EMERGE Measurement Guidelines Reports: “What is Measurement and How Do We Quantitatively Measure Gender Equality and Empowerment?” and “How to Create Scientifically Valid Social and Behavioral Measures on Gender Equality and Empowerment.”

Measure “Specs”:

  • What is the construct (concept or phenomena) trying to be measured?
  • How is it best measured (e.g., investigator observation, self-report, parent report)?
  • Do available measures exist?
  • If measures exist: What is the level of measurement (i.e., individual, neighborhood, state, and nation)?

[Keep in mind that index measures may be more useful to understand gender equality and empowerment issues at larger ecological units such as the state or country level whereas scales can be more useful to understand gender equality and empowerment as experienced at the individual level]

  • If measures exist: How do these measures compare in terms of scientific (psychometric) quality and use (citation frequency) in the literature?

[Keep in mind that single-item indicators tend to be less psychometric rigorous than multi-item measures and newly published measures need time to become widely “used” in the field]

Population Demographics:

Consider the following attributes of your target population

  • Gender
  • Age
  • Literacy
  • Cultural norms

Research Constraints:

Practical things all researchers should keep in mind:

  • Time for administration
  • Financial feasibility
  • Logistical aspects (e.g. place of interview)


Based on our recent efforts, we have identified several “high-ranking” measures that may be useful for research, evaluation, or educational purposes. For details on how score classifications were determined see Measurement: Scoring Methodology. Tags are organized such that the first score represents the measures psychometric score and the second score represents the measures citation frequency score. Measures tagged as “HIGH/HIGH” were both “HIGH” in terms of psychometric score and in terms of citation frequency.

In many respects, “HIGH/HIGH” tagged measures serve are strong measures. Still the selection of a measure should not only be based on its psychometric rigor and use in the literature but also based on the appropriateness of the measure as it relates to the construct of interest, population of interest, and researcher or study constraints. Thus, the user of the measure or instrument must always decide accounting for a diversity of factors which measure is “best.”

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