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Gender-Sensitive Family Health Project Design and Evaluation

This module discusses the importance of gender issues in designing and evaluating a family health project, including strategies for addressing gender sensitivity and ensuring design validity. It explores different types of research designs and their strengths and weaknesses in answering impact and causality questions.

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Gender-Sensitive Family Health Project Design and Evaluation

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  1. Module 3 Designs

  2. Family Health Project: Exercise Review Discuss the Family Health Case and these questions. • Consider how gender issues influence the formulation and implementation of the development of a family health project? • Consider some likely questions that you might ask if you wanted to monitor and/or evaluate this family health project? • What additional questions might you ask to make sure your questions are gender-sensitive? What other actions would you take?

  3. Learning Objectives At the end of this session participants will understand: • the importance of design in answering questions about impact • design options • gender issues as they relate to design

  4. Evaluation Research Design Type of Questions - Determine Strategy • For descriptive and normative question, strategy may be simple and straight forward. • For impact questions, how you will control for other factors so you can ascertain the effects of your program. • Impact questions require a different types of design.

  5. Designs for M&E Design = Strategy for answering M&E questions: • Did the program cause the changes you observe? • To answer this key causal question, you must be able to eliminate other explanations. • This is done through design which controls for other factors so you can measure the effect of your program.

  6. Design Validity • Judge the quality of the design by its validity • Two types of validity: • Internal validity • Is what you observe due to the program and not other factors? • External validity • Is what you observe true in the larger population?

  7. Threats to Internal Validity • History Due to a particular event that took place while data was being conducted. • Maturation Skills increase because people get older. • Testing Risk is that they “learned” how to do the test. • Instrumentation Changes in data collection instrument, procedures or measures.

  8. Threats to Internal Validity (Continued) • Regression to the Mean The next set of scores are likely to change – to fall closer to the mean– regardless of treatment. • Selection The group under study may be different in ways that effect the results. • Attrition Different rates of dropping out of the program may affect results.

  9. Threats to External Validity • Biased or non-representative sampleSample is selected that is different from the larger population. • Unique program Results are not likely to be the same elsewhere because of a unique program quality. • Unique setting Results are not likely to be the same in a different location.

  10. Types of Design • Experimental • Quasi-Experimental • Non-Experimental

  11. Types of DesignExperimental Design Ideal Design for Measuring Impact • Key elements: • Random Assignment to groups • Program group • Control group • Before and After Measurement • Strongest design because all other explanations (threats to internal validity) have been ruled out • May be a problem with external validity

  12. Types of DesignExperimental Design R O1 X O2 R O1 O2 R indicates Random assignment O is the Observation or measure X is the Program or the intervention

  13. Experimental Design Gender Issues in Answering Causality • Experimental design is the strongest for answering causal questions • But: • it can be flawed for examining gender issues if the group that is randomly assigned does not include both men and women • experimental studies of only men are not valid for conclusions about women

  14. Experimental Design Experimental Design is Rarely Used • It is often not possible to use experimental design. • ethics, practicality, costs • Other evaluation designs • Quasi-experimental • Non-experimental • Each successive design is weaker and more vulnerable to wrong interpretations of project impacts.

  15. Types of Design Quasi-Experimental Design O1 X O2 Program Group O1 O2 Control Group • Groups • No random assignment • Matched pairs • Non-equivalent comparison groups.

  16. Quasi-Experimental Design Using Statistical Controls • Collect data from a large sample or the whole population and then statistically create comparison groups • Are widowed women more likely to control resources than married women? • Are men more or less likely to repay loans than women? • Useful to measure program impact when it is not possible to randomly assign people to programs • Eliminates threats to external validity

  17. Types of Design Non-Experimental Design • Before and After Design (lacks control group): O X O • Static Group Comparison (lacks pre-measure): X O O • One Shot (lacks control group and pre-measure): X O

  18. Case Discussion Micro-Credit Studies • Economic Study: • Quasi-experimental design using statistical controls to create various comparison groups • Cross-sectional survey • No pre-test (baseline) data • Social Study: • Data collected from participants only after project was implemented • One-shot design: no comparison group, no pre-measures.

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