Research methods to challenge gender expectations

Participatory Research Toolkit: Empowering Communities to Measure Social Norms (#2, Research) This toolkit is a very rich resource for practitioners. Developed by #UNFPA and #UNICEF, provides invaluable resources to achieve this. It marks the culmination of SBC research conduct over many years. Why Participatory Methods? Participatory research methods empower participants by engaging them in discussions about complex and sensitive topics. This toolkit brings together nine participatory tools, offering practical guidance and examples to qualitatively measure social norms. Key Tools and Their Uses: Body Mapping: Visual aids help assess knowledge, attitudes, and behaviors concerning the body and mind. This method is particularly useful for understanding experiences related to physical and psychosocial factors. Cannot Do, Will Not Do, Should Not Do: Categorizes behaviors to reveal the reasons behind restrictions. This helps in identifying structural barriers, personal norms, and social norms. Complete-the-Story: Uses vignettes to allow participants to indirectly express their attitudes and intentions. This method is effective for discussing sensitive topics without asking participants to directly disclose their experiences. Free Listing: Participants list terms and concepts related to a given prompt, revealing how they conceptualize specific domains. This method is useful for formative research and understanding attitudes and norms. Gender Boxes and Gender Jumble: These tools measure gender norms and examine how gender impacts attitudes and behaviors. They are essential for research focused on the existence and influence of gender norms. Lifeline: Identifies normative cultural practices and provides a timeline of key life events. This tool is useful for research using a life-course perspective. Social Network Mapping: Visually represents reference groups across different levels of the social ecological model. This tool helps understand communication flow and social support within networks. 2x2 Tables for Social Norms: Measures the components of social norms (injunctive and descriptive norms, behavioral expectations, attitudes, and social rewards and sanctions) to understand norms on a deeper level. Real-World Applications: What is great about this toolkit is that provides examples of the tools have been used: .g. how Body Mapping was used to understand the physical and psychosocial risks of FGM in Ethiopia. This comprehensive guide shows that by leveraging these participatory methods, we can design more effective, culturally relevant programs that foster positive social change. My congratulations to the authors for pulling this incredibly useful set of tools together. Imagine using a tool called “Gender Jumble”. I can’t wait! #SocialNorms #ParticipatoryResearch #CommunityEngagement #BehaviorChange #ProgramDesign #UNFPA #UNICEF #TransformNorms Naveera Amjad Cäcilia Riederer

As participatory methods gain recognition in measuring complex social change, this document offers a rigorous and hands-on toolkit for assessing social norms through community-centered inquiry. It does not merely describe research techniques—it empowers users to adopt creative, inclusive, and context-sensitive tools to surface deep-rooted beliefs and practices. M&E professionals, program designers, and social norm practitioners are invited to treat data generation as a collective process of learning and transformation. Here, participation is not a means—it is the method itself for decoding and reshaping social expectations. – It defines participatory research as a method that prioritizes community voice in measuring and interpreting social norms – It introduces nine tools including Body Mapping, Gender Boxes, Lifeline, Social Network Mapping, and 2x2 Tables – It links each tool to specific constructs like injunctive norms, reference groups, stigma, and power dynamics – It emphasizes participatory analysis as a feedback loop for community learning and adaptive programming – It provides examples from UNICEF-supported programs in India, Ethiopia, Guinea, Macedonia, and Jamaica – It guides ethical engagement, data use, and safeguarding when working with children and marginalized groups – It integrates frameworks like ACT for social norms change around FGM and other harmful practices – It offers visual aids, step-by-step instructions, and interpretation models to support field-level application Bridging academic depth with operational usability, this toolkit transforms research into a shared journey of discovery and change. Each section enhances the ability to translate norms into evidence, voice into strategy, and behavior into measurable impact. More than a technical manual, it is a participatory instrument for social listening, accountability, and systemic empowerment.

In epidemiologic studies, measurement biases between genders can distort our understanding of health outcomes. Measurement scales, diagnostic criteria, and even data collection methods often reflect historical biases that favor one gender over another (e.g., may not capture gender-specific symptomology). This skewed approach has deep roots. Instead of the default being inclusion, the default was exclusion when it came to women in clinical trials—a choice driven by societal, cultural, and scientific biases. Concerns about reproductive health, like potential risks to fetuses or hormonal shifts from menstruation, were cited to bar women of childbearing age, even when irrelevant to the study. Male physiology was treated as the "standard," with trials overwhelmingly designed for men under the false assumption that gender differences in drug responses or side effects were trivial. Women’s hormonal variability was framed as a problem to avoid, and the absence of women in medical leadership cemented their exclusion for decades. The fix goes beyond solidarity statements on women's day. We need more inclusive approaches in study design: 1️⃣ Stratify by gender—and age—when sampling in clinical studies: Stratifying by gender during recruitment ensures enough women are included. But in some cases, gender alone isn’t enough—older women are often underrepresented, missing issues like perimenopause or menopause. Stratifying by age (e.g., <50 vs. 50+) and gender creates four groups—older men, younger men, older women, younger women—letting us probe treatment effects or disease patterns across diverse groups. 2️⃣ Test for effect modification by gender: Analyzing whether gender alters an intervention’s impact can reveal critical biological insights. If a treatment helps everyone but benefits one gender more, that’s a key finding, for better or for worse. 3️⃣ Seek female co-authors deliberately: Especially for women’s health topics, diverse teams matter. An all-male group risks missing key variables only flagged late (say, in peer review) because no one saw the female perspective. This can introduce unmeasured confounding. Once the work’s done, don’t judge author contributions by nouns or pronouns (Jack, Jill, him, her)—that’s the wrong lens. Focus on verbs and adverbs (analyzed, wrote, thoroughly, expertly): what was done and how well. 4️⃣ Power Studies for Subgroup Analysis: Design trials with enough statistical power to detect gender-specific differences, avoiding the trap of underpowered, one-size-fits-all conclusions. Gender sensitivity isn’t just about methods—it’s also about language. 🗣️ Words shape perception, and outdated terms entrench exclusion. Small shifts matter: ❌ Chairman → ✅ Chair or Chairperson ❌ Mankind → ✅ Humanity ❌ Man-made → ✅ Synthetic or Artificial ❌ Manpower → ✅ Personnel ❌ Layman → ✅ Layperson ❌ Middleman → ✅ Intermediary It’s time our science mirrors reality—for everyone. 🌍 #Chisquares #GenderBias #InclusiveResearch