proposal writing revised

Research Methodology (COMH503)

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Course Description

• This course introduces the principal concepts• This course introduces the principal conceptsand components of research.

• It deals with the ways how to define researchquestions, formulate problem statement,develop a research project proposal, how tocollect research data and analyze and interpretcollect research data and analyze and interpretdata.

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Course Objectives

By the end of the course, students will be able:• To Describe basic steps in undertaking health research• To exercise how to search and review literatures• To exercise how to search and review literatures• To demonstrate how to formulate problem statement and

research questions• To determine how to develop a research proposal• To determine the sample size required for a study• To explain how to collect research data and analyze it• To explain how to collect research data and analyze it• To describe ethics in health research• To formulate how to write and disseminate research findings

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Course Contents1. Introduction2. Types of research3. Components of a research

proposal

10. Sample size calculation11. Overview of sampling

methods12. Types of variablesproposal

4. Research questions and problem statement

5. Literature search and review

6. Formulating research hypothesis

7. Formulation of research

12. Types of variables13. Data collection techniques14. Designing research

questionnaire15. Bias in data collection16. Data management and

analysis17. Health research ethics7. Formulation of research

objectives8. Study designs9. Quantitative and

qualitative research methods

17. Health research ethics18. Scientific report writing19. Dissemination of research

findings

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Methods of Instruction and Evaluation

Methods of Instruction• Lectures and discussions• Lectures and discussions• In-class exercises• Take-home assignmentsEvaluation• Evaluation methods

– 10% Progressive assessment (class participation and attendance)attendance)

– 40% Preparation of a mini-research proposal on a given topic

– 50% Final examination

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REFERENCE

1. Shi L. Health Services Research Methods.1997, Delmar Publishers. SPH Library.1997, Delmar Publishers. SPH Library.

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What is research?

• Research - is the systematic collection, analysisand interpretation of data to answer a certainand interpretation of data to answer a certainquestion or solve a problem.

• Health research - is the application of principles of research on health.

• It is the generation of new knowledge using scientific method to identify and deal with scientific method to identify and deal with health problems and come up with better solutions to mitigate the prevailing problem.

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What is research?

• Health Systems Research is concerned withimproving the health of people andimproving the health of people andcommunities, by enhancing the efficiencyand effectiveness of the health system as anintegral part of the overall process of socio-economic development, with fullinvolvement of all partners.economic development, with fullinvolvement of all partners.

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Basic questions in health system

• What are health needs of people?

• What is the coverage of health interventions?• What is the coverage of health interventions?

• How can we use resources cost-effectively?

• How can we control environmental factors?

N.B. Without research answering these questions is unthinkable

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Basic questions---

• The major objective of HSR is to providehealth managers at all levels, as well ashealth managers at all levels, as well ascommunity members, with the relevantinformation they need to make decisions onhealth-related problems they are facing.

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Basic questions---

• Health policy makers may, for example, wantto know:to know:– What are the prospects for voluntary

community-based insurance? What wouldacceptable contributions for different incomegroups? Should the pooling of resources takeplace on a community or national basis?place on a community or national basis?

– How can user-fees be used as an instrument todirect demands for care to the appropriate level?

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Basic questions---

• Managers at district/provincial level may raise questions such as:questions such as:

– Why is neonatal mortality in certain districts much higher than in other districts?

• Hospital directors may ask:

– Why do we have such a high rate of complications – Why do we have such a high rate of complications during child birth? Are the first-line services available and adequate? Are our own services adequate? Are mothers coming late for delivery and, if so, why?

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Basic questions---

• Managers at village level may want to know:– How can we assist women with little or no

education so that they can effectively recognisethe symptoms of pneumonia and go in time tothe health centre with their children?

– How much community labour will be required toHow much community labour will be required tomanage the new water system?

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Characteristics of research

• It demands a clear statement of the problem.

• It requires clear objectives and a plan (it is notaimlessly looking for something in the hope thatyou will come across a solution).

• It builds on existing data, using both positiveand negative findings.and negative findings.

• New data should be systematically collectedand analyzed to answer the original researchobjectives.

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Basic Vs applied research

• The classical broad divisions of research are: basicand applied research.and applied research.

• Basic Research - is designed to extend the bases ofknowledge in a discipline, for the sake ofunderstanding itself. (E.g. cloning, satelliteresearches ).researches ).

• Applied Research - concentrates on findingsolutions to immediate problems of practicalnature.

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Approaches

• there are two basic approaches to research -quantitative approach and the qualitative approach.quantitative approach and the qualitative approach.

1. The quantitative approach involves the generation of data in quantitative form which can be subjected to rigorous quantitative analysis.

• This approach can be further sub-classified into • This approach can be further sub-classified into inferential, experimental and simulation approachesto research.

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Approaches

• The purpose of inferential approach to research is to form a data base from which to infer is to form a data base from which to infer characteristics or relationships of population.

• This usually means survey research where a sample of population is studied (questioned or observed) to determine its characteristics, and it observed) to determine its characteristics, and it is then inferred that the population has the same characteristics.

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Approaches• Experimental approach is characterised by much

greater control over the research environment andin this case some variables are manipulated toin this case some variables are manipulated toobserve their effect on other variables.

• Simulation approach involves the construction of anartificial environment within which relevantinformation and data can be generated.

• This permits an observation of the dynamicbehaviour of a system (or its sub-system) undercontrolled conditions.

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Approaches• The term ‘simulation’ refers to “the operation of a

numerical model that represents the structure of a numerical model that represents the structure of a dynamic process.

• Given the values of initial conditions, parameters and exogenous variables, a simulation is run to represent the behaviour of the process over time.represent the behaviour of the process over time.

• Simulation approach can also be useful in building models for understanding future conditions.

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Approaches2. Qualitative approach to research is concerned with

subjective assessment of attitudes, opinions andbehaviour.behaviour.

• Research in such a situation is a function ofresearcher’s insights and impressions.

• Such an approach to research generates results eitherin non-quantitative form or in the form which are notin non-quantitative form or in the form which are notsubjected to rigorous quantitative analysis.

• Generally, the techniques of focus group interviews,projective techniques and depth interviews are used.

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Qualitative and Quantitative Approaches…

Qualitative QuantitativeUsually Non-probability based sample

Typically a probability-based samplesample sample

Non-generalizable

Exploratory

Generalizable

Explanatory

Answers Why? How? Answers How many? When? Where?

Generate hypothesis

Process is inductive

Tests hypotheses

Process is deductiveProcess is inductive Process is deductive

Data are “rich” and time-consuming to analyze

Data are more efficient, but may miss contextual detail

Design may emerge as study unfolds

Design decided in advance

Researcher IS the instrument Various tools, instruments employed

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Mixed method

• Triangulation (Multi-method designs)• Corroboration – (to strengthen or support with • Corroboration – (to strengthen or support with

other evidence; make more certain)-(superior evidence if the result from triangulation is the same)

• Here is a metaphor for thinking about mixed research: research: “Construct one fish net out of several fish nets that have holes in them by laying them on top of one another. The "new" net will not have any holes in it. The use of multiple methods or approaches to research works the same way.”

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Main components of any research work

1. Preparing a research proposal

2. Fieldwork (i.e., data collection)

3. Analyzing data and preparing a research report

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A Research Proposal

• A research proposal is a document that presentsa plan for a project to reviewers for evaluation.a plan for a project to reviewers for evaluation.

– It can be a supervised project submitted toinstructors

– it can present a project proposed to a fundingit can present a project proposed to a fundingagency.

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A Research Proposal

• Its purpose is to convince reviewers

• Can he/she handle the project?

• Is it well thought?

• Reviewers have more confidence that plannedproject will be successfully completed if theproject will be successfully completed if theproposal is well written and organized, and ifyou demonstrate careful planning.

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A Research Proposal…

• A proposal describes the research problems andits importance, and gives detailed account of theits importance, and gives detailed account of themethods that will be used and why they areappropriate.

• The proposal for quantitative research has mostof the parts of the research report: a title, anof the parts of the research report: a title, anabstract, a problem statement, a literaturereview, a method or design section, and abibliography.

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A Research Proposal…

• The proposal has a plan for data collection andanalysis.analysis.

• It frequently includes a schedule of the steps tobe undertaken and estimates of the time andbudget required to carry out each step of theresearch.

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How do you think about a research topic?

• From personal experiences/observations • From personal experiences/observations

• By discussion with community/health workers

• By contacting researchers/experts on the topic

• By reading journals/articles’ recommendations

• From formal advertisement by organizations• From formal advertisement by organizations

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Criteria for selecting a research topic

1. Relevance: The topic chosen should be a priority problem:problem:

• Questions to be asked include:

– How large or widespread is the problem?

– Who is affected?

– How severe is the problem?– How severe is the problem?

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2. Avoidance of duplication: • Investigate whether the topic has been researched.• Investigate whether the topic has been researched.• If the topic has been researched, the results should

be reviewed to explore whether major questions that deserve further investigation remain unanswered.

• If not, another topic should be chosen.• If not, another topic should be chosen.

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3. Feasibility: • Consider the complexity of the problem and the • Consider the complexity of the problem and the

resources you will require to carry out the study.• Thought should be given first to personnel, time,

equipment and money that are locally available.

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4. Political acceptability:

• It is advisable to research a topic that has theinterest and support of the authorities.

• This will facilitate the smooth conduct of theresearch and increases the chance that theresults of the study will be implemented.results of the study will be implemented.

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5. Applicability of possible results andrecommendationsrecommendations

• This will depend not only on the blessing ofthe authorities but also on the availability ofresources for implementing therecommendations.recommendations.

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6. Urgency of data needed

• How urgently are the results needed for making a decision?

• Which research should be done first and which can be done late?which can be done late?

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7. Ethical acceptability

• We should always consider the possibility that we may inflict harm on others while carrying out research.

• Therefore, it will be useful to review the • Therefore, it will be useful to review the proposed study.

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Scales for rating research topics

1. Relevance1 = Not relevant2 = Relevant3 = very relevant

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2. Avoidance of duplication1 = Sufficient information already available2 = Some information available but major

issues not covered3 = No sound information available on which

to base problem-solvingto base problem-solving

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3. Feasibility

1 = Study not feasible considering available resources

2 = Study feasible considering available resourcesresources

3 = Study very feasible considering available resources

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4. Political acceptability

1 = Topic not acceptable

2 = Topic somewhat acceptable

3 = Topic fully acceptable

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5. Applicability

1 = No chance of recommendations being 1 = No chance of recommendations being implemented

2 = Some chance of recommendations being implemented

3 = Good chance of recommendations being 3 = Good chance of recommendations being implemented

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6. Urgency

1 = Information not urgently needed

2 = Information could be used but a delay of some months would be acceptable

3 = Data very urgently needed for decision-3 = Data very urgently needed for decision-making

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7. Ethical acceptability

1 = Major ethical problems

2 = Minor ethical problems

3 = No ethical problems

N.B. The above rating should be based on the existing N.B. The above rating should be based on the existing data and not on mere assumptions.

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Formulating the Problem Statement and Justification of the Problems

• The first major section in a research proposal is the‘statement of the problem’.‘statement of the problem’.

• It should describe the problem that is to be investigatedand the questions that will guide the research process.

• Note that proper justification of the importance of theresearch questions to be addressed requires some senseresearch questions to be addressed requires some senseof the likely contribution to knowledge that the researchwill make and its place in current debate or technologicaladvance.

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Formulating the Problem Statement and Justification of the Problems

• Often, this can be presented in the form of researchhypotheses to be tested.hypotheses to be tested.

• All research is set in motion by the existence of aproblem.

• A problem is a perceived difficulty, a feeling ofdiscomfort about the way things are, or a discrepancybetween what someone believes should be the situationbetween what someone believes should be the situationand what the situation is in reality.

• While problems are the initiating force behind research,not all problems require research.

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What is a research problem?...A potential research situation arises when three

conditions exist:-

1. A perceived discrepancy exists between what is and1. A perceived discrepancy exists between what is andwhat should be (e.g. malaria in highlanders andlowlanders).

2. A question exists about why there is a discrepancy.

3. At least two possible and plausible answers exist to the3. At least two possible and plausible answers exist to thequestion.

N.B. If there is only one possible and plausible answer tothe question about the discrepancy, then a researchsituation does not exist.

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Why is it important to state and definethe problem well?

Because a clear statement of the problem:-

• Is the foundation (blue print) for furtherdevelopment of the research proposal (researchobjectives, methodology, work plan, budget,etc).

• Makes it easier to find information and reportsof similar studies from which your own studydesign can benefit.

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Why is it important to state and definethe problem well?

• Enables you to systematically point out why theproposed research on the problem should beproposed research on the problem should beundertaken and what you hope to achieve with thestudy results.

• This is important to highlight when you presentyour project to community members, health staff,relevant ministries and donor agencies who needto support your study or give their consent.

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What information should be includedin the problem statement?

1. A brief description of socio-economic and culturalcharacteristics and an overview of health status and thecharacteristics and an overview of health status and thehealth-care system in the country/district and Include afew illustrative statistics.

2. A concise description of the nature of the problem, thesize, distribution and severity of the problem.

3. An analysis of the major factors that may influence theproblem and a discussion of why certain factors needmore investigation if the problem is to be fullyunderstood.

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What information should be includedin the problem statement?

4. A brief description of any solutions to the problem thathave been tried in the past, how well they havehave been tried in the past, how well they haveworked, and why further research is needed(justification for your study).

5. A description of the type of information expected toresult from the project and how this information will beresult from the project and how this information will beused to help solve the problem.

6. If necessary, a short list of definitions of crucialconcepts used in the statement of the problem.

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How to write a Problem Statement

• The section should be precise and concise,while not forgetting to mention essentialwhile not forgetting to mention essentialpoints.

• Information concerning the problem shouldbe summarized, so the reader is not“drowned” in detail.

• An outline listing the major points to be• An outline listing the major points to becovered could be prepared before any writingis done, so the section will be logical and wellorganized.

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Review of Literature• For any serious study, a thorough literature review

must be accomplished. However, the questionmust be accomplished. However, the questionremains: Why Review?

• To which point in the theoretical agenda of thatbody of knowledge does your project relate tomost directly?

• What are the major controversies that are• What are the major controversies that areimportant for your project? --you need to do acomprehensive and focused literature review onyour particular topic.

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The result of the literature review should be:

• A reaffirmation of the importance of thetheoretical rationale of the project in the lighttheoretical rationale of the project in the lightof the work of others in the same area, and;

• An emphasis on the contribution which theproject is likely to make to the ongoing task ofbuilding and improving theory in a given area ofknowledge.knowledge.

• The later should be your target!

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Why is a review of literature important when preparing a proposal?

• It helps further your understanding of theproblem and may lead to refining of theproblem and may lead to refining of the“Statement of the problem”.

• It helps you find out what others have learnedand reported on your topic, and take account ofthis in the design of your study.this in the design of your study.

• It gives you a familiarity with the various typesof methodology that might be used in yourstudy.

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What resources can be consulted for thereview of the literature?

• Card catalogues of books in libraries

• Indexes such as INDEX MEDICUS,INTERNATIONAL NURSING INDEX etc. thatidentify journal articles by subject, author andtitle.

• Summaries of abstracts of books and articles• Summaries of abstracts of books and articles

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What resources ---?

• Computer-based literature searches such asMEDLINE, PUBMED.MEDLINE, PUBMED.

• Bibliographies such as those found at the end ofbooks, articles, theses, etc. or prepared asseparate documents.

• Statistics collected at the national, provincial• Statistics collected at the national, provincialand/or departmental levels.

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What resources ---?

• Studies conducted in the country or region.

• Responses to enquiries on ongoing research.

• Theoretical works related to the topic.

• Works on methodology and descriptions ofmethodologies used in other studiesmethodologies used in other studies

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What resources ---?

• Responses from agencies willing to supplyreference materials for research by mail.reference materials for research by mail.

• Opinions, beliefs, points-of-view.

• Anecdote, clinical observations, reports ofincidents

• Gray literature etc.

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• After collecting the required information theinvestigator should decide in which orderhe/she wants to discuss previous researchhe/she wants to discuss previous researchfindings:

– from global to local

– from broader to focused

– from past to current

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• This review should answer

– How much is known?

– What is not known?– What is not known?

– What should be done based on what islacking?

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Methods of citations in preparingliterature review:

• Information on an index card should be organized insuch a way that you can easily find all the data you willsuch a way that you can easily find all the data you willneed for your report:

• For an article the following information should benoted:

• Author(s)’ Surname followed by initials. Title of article.Name of Journal. Year, Volume, (number): pageName of Journal. Year, Volume, (number): pagenumbers of article.

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Methods of citations in preparingliterature review:

Example:Example:

• Louria DB. Emerging- and re-emerging infections: Thesocietal variables. International Journal of InfectiousDisease. 1996, 1(2):59-62.

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Methods of citations…

• For a book the following information shouldbe noted:be noted:

• Author(s)’ Surname followed by initials. Titleof book. Place: Publisher, Year, Edition

Example:• Abramson JH. Survey methods in community• Abramson JH. Survey methods in community

medicine. Edinburgh: Churchill Livingstone,1990, 4th ed.

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Vancouver Vs Harvard system

• The formats suggested above have beenadopted as standard by over 300 biomedicaladopted as standard by over 300 biomedicaljournals and are referred to as the VancouverSystem.

• In other journals and books it is common toput the year, between brackets, straight afterput the year, between brackets, straight afterthe name of the author(s).

• This is called the Harvard System.

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Vancouver Vs Harvard…

• In Harvard style, this looks as follows:

• Abramson JH (1990) 4th ed. Survey methods in community medicine. Edinburgh: Churchill Livingstone.

• N.B. Alphabetical referencing

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RESEARCH OBJECTIVES

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RESEARCH OBJECTIVES

• The OBJECTIVES of a research project summarisewhat is to be achieved by the study.what is to be achieved by the study.

• Objectives should be closely related to thestatement of the problem.

• For example, if the problem identified is lowutilisation of child welfare clinics, the generalutilisation of child welfare clinics, the generalobjective of the study could be to identify thereasons for this low utilisation, in order to findsolutions.

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RESEARCH OBJECTIVES

• The general objective of a study states whatresearchers expect to achieve by the study inresearchers expect to achieve by the study ingeneral terms.

Specific objectives

• It is possible (and advisable) the break down a• It is possible (and advisable) the break down ageneral objective into smaller, logically connectedparts.

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RESEARCH OBJECTIVES

• Specific objectives should systematically addressthe various aspects of the problem as defined underthe various aspects of the problem as defined underStatement of the Problem and the key factors thatare assumed to influence or cause the problem.

• They should specify what you will do in your study,where and for what purpose.where and for what purpose.

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RESEARCH OBJECTIVES

• A study into the cost and quality of home-basedcare for HIV/AIDS patients and their communities incare for HIV/AIDS patients and their communities inEthiopia, for example, has as its general objective:

“To explore to what extent community home-based care (CHBC) projects in Ethiopia provideadequate, affordable and sustainable care ofgood quality to people with HIV/AIDS, and togood quality to people with HIV/AIDS, and toidentify ways in which these services can beimproved”.

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RESEARCH OBJECTIVES

• It was split up in the following specific objectives:

1. To identify the full range of economic,psychosocial, health/nursing care and other needsof patients and their families affected by AIDS.

2. To determine the extent to which formal andinformal support systems address these needsinformal support systems address these needsfrom the viewpoint of service providers as well aspatients.

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RESEARCH OBJECTIVES

3. To determine the economic costs of CHBC to the patient and family as well as to the formal CHBC patient and family as well as to the formal CHBC programmes themselves.

4. To relate the calculated costs to the quality of care provided to the patient by the family and to the family/patient by the CHBC programme.

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RESEARCH OBJECTIVES

5. To determine how improved CHBC and informalsupport networks can contribute to the needs ofsupport networks can contribute to the needs ofpersons with AIDS and other chronically andterminally ill patients.

6. To use the findings to make recommendations onthe improvement of CHBC to home care providers,donors and other concerned organisations,donors and other concerned organisations,including government.

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Why should research objectives be developed?

The formulation of objectives will help you to:

1. Focus the study (narrowing it down to essentials);

2. Avoid the collection of data which are not strictly necessary for understanding and solving the problem you have identified; andthe problem you have identified; and

3. Organise the study in clearly defined parts or phases.

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Why should research objectives be developed?

• Properly formulated, specific objectives willfacilitate the development of your researchfacilitate the development of your researchmethodology and will help to orient thecollection, analysis, interpretation andutilisation of data.

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How should you state your objectives?

• Take care that the objectives of your study:

1. Cover the different aspects of the problem and its 1. Cover the different aspects of the problem and its contributing factors in a coherent way and in a logical sequence;

2. Are clearly phrased in operational terms, specifying exactly what you are going to do, where, and for what purpose;what purpose;

3. Are realistic considering local conditions; and

4. Use action verbs that are specific enough to be evaluated.

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How should you state your objectives?

• Keep in mind that when the project isevaluated, the results will be compared toevaluated, the results will be compared tothe objectives.

• If the objectives have not been spelled outclearly, the project cannot be evaluated.

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How should you state your objectives?• Using the previous example on cost and quality of

CHBC, we may develop more specific researchquestions for the different objectives, such as:questions for the different objectives, such as:

1. Do rural and urban CHBC projects differ withrespect to the adequacy, quality, affordability andsustainability of HBC provided?

2. How satisfied are AIDS patients, relatives and2. How satisfied are AIDS patients, relatives andservice providers with the care provided? Arethere differences in perceptions between thosegroups?

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How should you state your objectives?3. Is the stigma attached to being HIV+ the same

strong for women as for men? Or are there genderdifferences in stigma?differences in stigma?

4. What impact does the care provided to AIDSpatients have on the economy of the homestead?Is there competition with other basic needs (e.g.schooling of children, purchases of food)?

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Types of objectives

1. Estimation objectives – Estimates magnitude of an event– Estimates magnitude of an event

2. Association objectives – Analyses factors associated with an event

3. Evaluation objectives Evaluates associations– Evaluates associations

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When should the objectives of aresearch project be prepared?

• The objectives should be written after the• The objectives should be written after thestatement of the problem is developed, i.efollowing the literature review, and before themethodology for the study is planned.

• Because the objectives show the precise goal ofthe study, help guide the development of thethe study, help guide the development of theresearch methodology, and orient thecollection, analysis and interpretation of data.

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What are the characteristics of goodobjectives?

Objectives should be:– Logical and coherent– Logical and coherent– Feasible (few objectives)– Realistic, considering local conditions– Defined in operational terms that can be

measuredmeasured– Phrased to clearly meet the purpose of the study

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How should objectives be stated?

• Objectives should be stated using “action verbs”that are specific enough to be measured:that are specific enough to be measured:

Examples:

• To determine …, To compare…, To verify…, Tocalculate…, To describe…, etc.calculate…, To describe…, etc.

• Do not use vague non-action verbs such as:

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Action-verbs Vs non-action verbs

Action-verbsTo determine To compare To verifyTo determine To compare To verifyTo calculate To describe To assesTo explore To test To establish To identify

Non-action verbsTo appreciate To understand To showTo share To believe to study

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What formats can be used for statingresearch objectives?

• Research objectives can be stated as:

– Questions: “The objectives of this study are toanswer the following questions …”

– Positive sentence: “The objectives of this studyare to determine …”

– Hypothesis: “The objective of this study is toverify the following hypothesis...”

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Research hypothesis

What is a Research Hypothesis?

• A hypothesis can be defined as “a tentativeprediction or explanation of the relationshipbetween two or more variables and theproblem under study that can be tested.

• A hypothesis, in other words, translates theproblem statement into a precise, unambiguouspredication of expected outcomes.”

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Research hypothesis

• Based on your experience with the studyproblem, it might be possible to developproblem, it might be possible to developexplanations for the problem, which can thenbe tested.

• If so, you can formulate hypotheses inaddition to the study objectives.addition to the study objectives.

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Research hypothesis• In the example concerning the cost and quality of HBC

in Ethiopia it would have been possible to formulateand test the following hypotheses:and test the following hypotheses:

1. The role of first-line relatives in the provision of careto AIDS patients is more substantial in rural than inurban areas.

2. The silence and stigma surrounding AIDS makes the2. The silence and stigma surrounding AIDS makes theformation of self-help groups of AIDS patients andtheir relatives next to impossible, which in turnmaintains the high level of stigma on HIV/AIDS.

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Research hypothesis

• Hypothesis statements are most applicable forfield intervention or evaluative studies.field intervention or evaluative studies.

• Diagnostic or exploratory studies do notnormally require hypothesis statementsbecause they generally do not test relationshipsbetween variables.between variables.

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What is a Research Hypothesis?...• They indicate the major independent and

dependant variables of interest.dependant variables of interest.

• They suggest the type of data that must becollected and the type of analysis that mustbe conducted in order to measure therelationship among the variables.relationship among the variables.

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Stating Research Hypotheses:

• A hypothesis can be simple in form, predicating therelationship between one independent and onerelationship between one independent and onedependant variable.

• “Health education involving active participation bymothers will produce more positive changes in childfeeding than health education based on lectures.”

• Independent variable: Type of health education

• Dependant variable: Changes in child feeding

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Stating Research Hypotheses:…

• A hypothesis can be stated in the form of “null” (Ho)

• In the alternative form (Ha).

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METHODS

• The methodology of a research project is the• The methodology of a research project is thecore of the study.

• The following are important questions toconsider when beginning to prepare a researchdesign for a research proposal:---------design for a research proposal:---------

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METHODS…

• What do I want to measure?• How can I measure it?• How can I measure it?• Where should I measure it?• What will I do with the answers collected?• How can I check whether my methods for measuring are

correct before beginning a large study?• What professional and non-professional staff do I need to

carry out this study?carry out this study?• What types of logistical support do I need?• Are there any ethical problems related to the study?• How can I avoid introducing biases into the study?• What constraints may affect this study?

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Components of a research design that should beaddressed in the methodology section of aresearch proposal:• Study area• Research designs• Research designs• Variables• Sampling method• Plan for data collection• Plan for analysis of data and interpretation of the

resultsresults• Staffing, supplies and equipment (covered in

detail in ‘Budget and plan for data collection andanalysis’ section).

• Ethical considerations94Hunachew B

Variables• What information are we going to collect in our

study to meet our objectives?

• In most studies, we must first describe theproblem itself more precisely.

• For example, in a study that is investigating whyso many tuberculosis (TB) patients default fromout-patient treatment, we first want to knowout-patient treatment, we first want to knowhow high the defaulter rate is: is it 10%, 30%,50%?

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Variables• To obtain the defaulter rate we need a clear

definition of what we mean by defaultingdefinition of what we mean by defaulting(how many times treatment was missed).

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Variables• We also want to know whether certain factors do

indeed influence the problem, and to what extent.indeed influence the problem, and to what extent.

• If we know the extent to which a certain factorinfluences the problem, we are much more likely tobe able to convince ourselves (and relevant others)to take action.to take action.

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Variables• For example, if we find that becoming a dropout of TB

treatment is strongly associated with the followingfactors, we have clues that will help us to solve thefactors, we have clues that will help us to solve theproblem:

• The patient’s lack of knowledge concerning the actualduration of treatment and the danger of relapse or deathwhen the full course is not completed;

• Living more than 8 km away from the clinic where the• Living more than 8 km away from the clinic where thedrugs have to be collected monthly; and

• Being between 15 and 30 years of age.

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Variables• To find these associations between problems and

contributing factors, it is essential that we carefullydefine the problem itself, as well as each of thedefine the problem itself, as well as each of thefactors identified when analysing the problem .

• We do this by formulating variables.

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FORMULATING VARIABLES• A variable is a characteristic of a person, object or

phenomenon which can take on different values.

• These may be in the form of numbers (e.g., age) or non-numerical characteristics (e.g., sex).

• A simple example of a variable in the form of numbers is ‘a person’s age’.

• The variable ‘age’ can take on different values since a person can be 20 years old, 35 years old and so on.

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FORMULATING VARIABLESOther examples of variables are:

– weight (expressed in kilograms or in pounds);– weight (expressed in kilograms or in pounds);

– home - clinic distance (expressed in kilometres or in minutes walking distance);

– monthly income (expressed birr); and

– number of children (1, 2, etc.).

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FORMULATING VARIABLES• Because the values of all these variables are

expressed in numbers, we call them numerical expressed in numbers, we call them numerical variables.

• Some variables may also be expressed in categories.

• For example, the variable sex has two districts categories, groups - male and female.

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FORMULATING VARIABLES• Other examples are:

• Colour• Colour

– Red

– Blue

– green, etc.– green, etc.

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FORMULATING VARIABLES• Outcome of disease

– Recovery– Recovery

– chronic illness

– death

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FORMULATING VARIABLES• Main type of staple food eaten

– Maize– Maize

– Millet

– Rice

– cassava, etccassava, etc

• Since these variables are expressed in categories, we call them categorical variables.

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FORMULATING VARIABLES

• Numerical variables can either be continuousor discrete.or discrete.

Continuous.

• height in centimetres (2.5 cm or 2.546 cm or 2.543216 cm)

• temperature in degrees Celsius (37.2 0C or 37.19999 0C etc.)

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FORMULATING VARIABLESDiscrete- These are variables in which numbers can only have full values, numbers can only have full values,

• number of visits to a clinic (0, 1, 2, 3, 4, etc).

• number of sexual partners (0, 1, 2, 3, 4, 5, etc.)etc.)

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• Categorical variables, on the other hand, can either be ordinal or nominal.either be ordinal or nominal.

i. Ordinal variables. These are grouped variables that are ordered or ranked in increasing or decreasing order:

• High income (above 300 per month);• High income (above 300 per month);

• Middle income (100-300 per month); and

• Low income (less than 100 per month).108Hunachew B


• Other examples are:

• Disability: no disability, partial disability, • Disability: no disability, partial disability, serious or total disability

• Seriousness of a disease: severe, moderate, mildmild

• Agreement with a statement: fully agree, partially agree, fully disagree

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• Fear of leprosy: will not share food with a patient; will not enter the house of a patient; patient; will not enter the house of a patient; will not allow patient to live in the community.

• Note: Fear of leprosy is an attitude, and • Note: Fear of leprosy is an attitude, and attitudes are often scaled (you make them into ordinal variables).

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• If a researcher has little idea about thedistribution of a certain variable in adistribution of a certain variable in apopulation (for example, if you don’t knowwhether 30%, 50%, or 95% are below thepoverty line of 100 per month), it is advisableto categorise numerical data only after thepre-test, or even after data collection.to categorise numerical data only after thepre-test, or even after data collection.

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ii. Nominal variables. The groups in these variables do nothave an order or ranking in them.have an order or ranking in them.

For example:

• Sex: male, female

• Main food crops: maize, millet, rice, etc.

• Religion: Christian, Moslem, Hindu, Buddhism, etc.• Religion: Christian, Moslem, Hindu, Buddhism, etc.

• For examples of scales of measurement, as continuous,discrete, ordinal and nominal data require differentstatistical tests.

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Factors rephrased as variables

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Operationalizing variables by choosing appropriate indicators

• Operationalizing variables means that you make themmeasurable:measurable:

• For example:

• In many HSR studies, you want to determine the levelof knowledge concerning a specific issue in order tofind out to what extent the factor ‘poor knowledge’find out to what extent the factor ‘poor knowledge’influences the problem under study (for example lowutilisation of pre-natal care by pregnant women).

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Operationalizing variables bychoosing appropriate indicators

• The variable ‘level of knowledge’ cannot be measuredas such.as such.

• You would need to develop a series of questions toassess a woman’s knowledge, for example on pre-natal care and risk factors related to pregnancy.

• The answers to these questions form an indicator of• The answers to these questions form an indicator ofsomeone’s knowledge on this issue, which can thenbe categorised.

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• If 10 questions were asked, you might decidethat the knowledge of those with:that the knowledge of those with:

– 0 to 3 correct answers is poor,

– 4 to 6 correct answers is reasonable, and

– 7 to 10 correct answers is good.

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• Nutritional status of under-5 year olds is anotherexample of a variable that cannot be measuredexample of a variable that cannot be measureddirectly and for which you would need to chooseappropriate indicators.

• Widely used indicators for nutritional status include:

– Weight in relation to age (W/A)

– Weight in relation to height (W/H)– Weight in relation to height (W/H)

– Height in relation to age (H/A)

– Upper-arm circumference (UAC)

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• For the classification of nutritional status,internationally accepted categories already exist,internationally accepted categories already exist,which are based on so-called standard growth curves.

• For the indicator ‘Weight/Age’, for example, childrenare:

– well-nourished if they are above 80% of the standard,

– moderately malnourished if they are between 60% and80%, and

– severely malnourished if they are below 60%.

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Defining variables and indicators of variables

• To ensure that everyone (the researcher, thedata collectors, and eventually, the reader ofdata collectors, and eventually, the reader ofthe research report) understands exactlywhat has been measured and to ensure thatthere will be consistency in themeasurement, it is necessary to clearlymeasurement, it is necessary to clearlydefine the variables (and indicators ofvariables).

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Defining variables and indicators of variables

• For example, to define the indicator ‘waitingtime’ it is necessary to decide what will betime’ it is necessary to decide what will beconsidered the starting point of the ‘waitingperiod’ e.g., is it when the patient enters thefront door, or when he has been registeredand obtained his card?

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Fig. Relationship between qualitative and quantitative studies inunderstanding and measuring problems

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Dependent and independent variables

• The variable that is used to describe ormeasure the problem under study is calledmeasure the problem under study is calledthe dependent variable.

• The variables that are used to describe ormeasure the factors that are assumed tocause or at least to influence the problem arecalled the independent variables.

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• For example, in a study of the relationshipbetween smoking and lung cancer, ‘sufferingbetween smoking and lung cancer, ‘sufferingfrom lung cancer’ (with the values yes, no)would be the dependent variable and‘smoking’ (varying from not smoking tosmoking more than three packets a day) theindependent variable.

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• Whether a variable is dependent or independent isdetermined by the statement of the problem anddetermined by the statement of the problem andthe objectives of the study.

• It is therefore important when designing ananalytical study to clearly state which variable is thedependent and which are the independent ones.dependent and which are the independent ones.

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• Note that if a researcher investigates whypeople smoke, ‘smoking’ is the dependentpeople smoke, ‘smoking’ is the dependentvariable, and ‘pressure from peers to smoke’could be an independent variable.

• In the lung cancer study ‘smoking’ was the• In the lung cancer study ‘smoking’ was theindependent variable.

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• A variable that is associated with the problem andwith a possible cause of the problem is a potential

Confounding variable

with a possible cause of the problem is a potentialconfounding variable.

• A confounding variable may either strengthen orweaken the apparent relationship between theproblem and a possible cause.

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• in order to give a true picture of cause and effect,possible confounding variables must be considered,possible confounding variables must be considered,either at planning stage or while doing data analysis.

For example:

• A relationship is shown between bottle-feeding anddiarrhea in under-twos.diarrhea in under-twos.

• However, mother’s education may be related tobottle-feeding as well as to diarrhea.

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• In order to give a true picture of the relationshipbetween bottle-feeding and diarrhea of under-twos,between bottle-feeding and diarrhea of under-twos,the influence of mother’s education should becontrolled.

• This could either be addressed in the research design,e.g., by selecting only mothers with a specific level ofeducation, or it could be taken into account duringeducation, or it could be taken into account duringthe analysis of the findings by analysing the relationbetween bottle-feeding and diarrhea separately formothers with different levels of education.

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Background variables• In almost every study, background variables, such as

age, sex, educational level, socioeconomic status,marital status and religion, should be considered.marital status and religion, should be considered.

• These background variables are often related to anumber of independent variables, so that theyinfluence the problem indirectly (hence they arecalled background variables).

• Only background variables important to the studyshould be measured.

• Background variables are notorious ‘confounders’.

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Quantitative data collection Techniques

• Interview administered questionnaire • Interview administered questionnaire

• Self-administered questionnaire

• Direct measurement • Direct measurement

• Review of record

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Quantitative data collection Techniques

• Interview administered questionnaire

• Self-administered questionnaire

• Direct measurement

• Review of record

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Qualitative data collection Techniques

• Key informant interview • Key informant interview

• In-depth interview

• Focus group discussions • Focus group discussions

• Observations (direct, participant)

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RESEARCH METHODS

Study designs

• A study design is the process that guides• A study design is the process that guidesresearchers on how to collect, analyze and interpretobservations.

• It is a logical model that guides the investigator inthe various stages of the research.

• Several classifications of study types are possible,depending on what research strategies are used.

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• Non-intervention (Observational) studies in whichthe researcher just observes and analysesresearchable objects or situations but does notintervene; and

• Intervention studies in which the researchermanipulates objects or situations and measures theoutcome of his manipulations (e.g., byimplementing intensive health education andmeasuring the improvement in immunisationmeasuring the improvement in immunisationrates.)

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Non-intervention studies could be: exploratory, descriptive or analytical

1. Exploratory studies1. Exploratory studies

• An exploratory study is a small-scale study of relatively short duration, which is carried out when little is known about a situation or a problem.

• It may include description as well as comparison.

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For example:

• A national AIDS Control Programme wishes toestablish counselling services for HIV positive andestablish counselling services for HIV positive andAIDS patients, but lacks information on specificneeds patients have for support.

• To explore these needs, a number of in-depthinterviews are held with various categories ofpatients (males, females, married and single) andpatients (males, females, married and single) andwith some counsellors working on a programmethat is already under way.

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• When doing exploratory studies we describe theneeds of various categories of patients and thepossibilities for action.

• We may want to go further and try to explain the• We may want to go further and try to explain thedifferences we observe (e.g., in the needs of male andfemale AIDS patients) or to identify causes ofproblems.

• Then we will need to compare groups.

• Comparison is a fundamental research strategy toidentify variables that help explain why one group ofpersons or objects differs from another.

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• In HSR, small-scale studies that compareextreme groups are very useful for detectingmanagement problems.

• We could, for example, compare:

– Two district health teams that are functioningwell and two that do not function satisfactorily,in order to detect the possible reasons forbottlenecks in the functioning of the districtbottlenecks in the functioning of the districthealth teams;

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– One community with high and another with lowparticipation in health activities, in order toidentify factors that contribute to communityparticipation;participation;

– 20 mothers who delivered in a maternity and 20who delivered at home, in order to identifypossible reasons for the low percentage ofsupervised deliveries.supervised deliveries.

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• Exploratory studies gain in explanatory value if weapproach the problem from different angles at thesame time. This is called triangulation.

• In a study that is looking for causes of the lowpercentage of supervised deliveries, it may be veryuseful to include observations and interviews withhealth staff in the maternity centres that shouldserve the mothers in question and interviews withserve the mothers in question and interviews withtheir supervisors, as well as with the mothersthemselves.

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• In this manner, information from differentindependent sources can be cross-checked.

• If the problem and its contributing factors are• If the problem and its contributing factors arenot well defined it is always advisable to doan exploratory study before embarking on alarge-scale descriptive or comparative study.

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2. Descriptive studies:

• A descriptive study involves describing thecharacteristics of a particular situation, eventcharacteristics of a particular situation, eventor case.

• Descriptive studies can be carried out on asmall or larger scale.

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a. Small scale, descriptive case studies

• Descriptive case studies describe in-depth thecharacteristics of one or a limited number ofcharacteristics of one or a limited number ofcases.

• A case may be, for example, a patient, a healthcentre, or a village.

• Such a study can provide quite useful insight• Such a study can provide quite useful insightinto a problem.

• Case studies are common in clinical medicine.

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b. Large scale, cross-sectional surveys

• Cross-sectional surveys aim at describing andquantifying the distribution of certain variables in astudy population at one point of time.study population at one point of time.

They may cover, for example:

i. Physical characteristics of people, materials or theenvironment, as in

– prevalence surveys (of bilharzia, leprosy, HIV), or– prevalence surveys (of bilharzia, leprosy, HIV), or

– evaluation of coverage (of immunisation,latrines, etc.),

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b. Large scale, cross-sectional ---

ii. Socio-economic characteristics of people such astheir age, education, marital status, number ofchildren and income,

iii. The behaviour or practices of people and theknowledge, attitudes, beliefs, opinions which mayhelp to explain that behaviour (KAP studies), or

iv. Events that occurred in the population.

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• Cross-sectional surveys cover a selected sample ofthe population.

• If a cross-sectional study covers the total populationit is called a census.

• A cross-sectional survey may be repeated in orderto measure changes over time in the characteristicsthat were studied.that were studied.

• The surveys may be very large, with hundreds oreven thousands of study units.

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• In these cases only a limited number of variableswill usually be included, in order to avoid problemswith analysis and report writing. If cross-sectionalsurveys are smaller they can be more complex.

• Small surveys can reveal interesting associationsbetween certain variables, such as between havingtuberculosis and socioeconomic status, sex, andways of coping.

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3. Comparative or analytical studies

• An analytical study attempts to establishcauses or risk factors for certain problems.causes or risk factors for certain problems.

• This is done by comparing two or moregroups, some of which have or develop theproblem and some of which have not.

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There are three commonly used types of analytical studies

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1. Cross-sectional comparative studies• Many cross-sectional surveys focus on describing as

well as comparing groups.

• For example, a survey on malnutrition may wish to• For example, a survey on malnutrition may wish toestablish:

– The percentage of malnourished children in acertain population;

– Socio-economic, physical, political variables that– Socio-economic, physical, political variables thatinfluence the availability of food;

– Feeding practices; and the knowledge, beliefs,opinions that influence these practices.

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1. Cross-sectional comparative ---

• The researcher will not only describe thesevariables but, by comparing malnourished and wellnourished children, he will try to determine whichsocio-economic, behavioural and otherindependent variables may have contributed tomalnutrition.

• In any comparative study, one has to watch out forconfounding or intervening variables.

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2. Case-control studies• In a case-control study the investigator compares

one group among whom the problem that hewishes to investigate is present (e.g. malnutrition)wishes to investigate is present (e.g. malnutrition)and another group called a control or comparisongroup, where the problem is absent, in order to findout what factors have contributed to the problem.

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Fig. Diagram of a case-control study

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• For example, in a study of the causes of neonataldeath, the investigator will first select the cases(children who died within the first month of life)and controls (children who survived their firstand controls (children who survived their firstmonth of life).

• (S)he then interviews their mothers to compare thehistory of these two groups of children, todetermine whether certain risk factors are moreprevalent among the children who died than amongprevalent among the children who died than amongthose who survived.

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• Controls should come from the same sourcepopulation.

• For example, in a hospital case-control study where• For example, in a hospital case-control study wherecases are being sought in the hospital, control shouldnormally be selected from patients attending at thesame hospital.

• If controls are selected from another hospital, theymight not be from the same source populationmight not be from the same source populationbecause the referral pathways may be different, andtherefore they would not really be comparable to thecases.

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3. Cohort studies

• In a cohort study, a group of individuals that isexposed to a risk factor (study group) is comparedto a group of individuals not exposed to the riskfactor (control group).

• The researcher follows both groups over time andcompares the occurrence of the problem that heexpects to be related to the risk factor in the twoexpects to be related to the risk factor in the twogroups to determine whether a greater proportionof those with the risk factor are indeed affected.

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3. Cohort studies

• example of a cohort study - smokers and non-smokers that is conducted among doctors tosmokers that is conducted among doctors todetermine the importance of smoking as arisk factor for developing lung-cancer.

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Figure: Diagram of a cohort study

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2. Intervention studies• In intervention studies, the researcher manipulates a

situation and measures the effects of this manipulation.

• Usually (but not always) two groups are compared, one• Usually (but not always) two groups are compared, onegroup in which the intervention takes place (e.g.treatment with a certain drug) and another group thatremains untouched (e.g. treatment with a placebo).

• The two categories of intervention studies are:

a. experimental studies and

b. quasi-experimental studies

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1. Experimental studies

• An experimental design is a study design that givesthe most reliable proof for causation.

• individuals are randomly allocated to at least two• individuals are randomly allocated to at least twogroups.

• One group is subject to an intervention, orexperiment, while the other group(s) is not.

• The outcome of the intervention (effect of theintervention on the dependent variable/problem) isobtained by comparing the two groups.

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Figure: Diagram of an experimental study

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• A number of experimental study designs have beendeveloped. These are widely used in laboratorysettings and in clinical settings.

• For ethical reasons, the opportunities forexperiments involving human subjects arerestricted.

• However, randomised control trials of new drugsare common.

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• For example, a researcher plans to study the effectof a new drug. (The drug has already been testedextensively on animals and has been approved fortrial use.)trial use.)

• He plans to include 300 patients in the study whoare currently receiving the standard treatment forthe same condition for which the new drug hasbeen designed.been designed.

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• He explains the study to the patients asking their consent to be divided into two groups on a random basis.

• One group will receive the experimental drug while • One group will receive the experimental drug while the other group will continue to receive the standard treatment.

• He makes sure that the medications are disguised and labelled in such a manner that neither the research assistant administering them nor the research assistant administering them nor the patient know which drug is used. (This is called a double blind experiment.)

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• At community level, where HSR is frequentlyundertaken, we experience not only ethical but alsopractical problems in carrying out experimentalstudies.studies.

• In real life settings, it is often impossible to assignpersons at random to two groups, or to maintain acontrol group.

• Therefore, experimental research designs may haveto be replaced by quasi-experimental designs.to be replaced by quasi-experimental designs.

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2. Quasi-experimental studies• In a quasi-experimental study, one characteristic of

a true experiment is missing, either randomisationa true experiment is missing, either randomisationor the use of a separate control group.

• A quasi-experimental study, however, alwaysincludes the manipulation of an independentvariable which is the intervention.variable which is the intervention.

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• One of the most common quasi-experimentaldesigns uses two (or more) groups, one of whichserves as a control group in which no interventiontakes place.takes place.

• Both groups are observed before as well as afterthe intervention, to test if the intervention hasmade any difference.

• (This quasi-experimental design is called the ‘non-• (This quasi-experimental design is called the ‘non-equivalent control group design’ because thesubjects in the two groups (study and controlgroups) have not been randomly assigned.)

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Figure : Diagram of a quasi-experimental design with two groups

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• Example of a quasi-experimental study:

• A researcher plans to study the effects of health education on the levelof participation of a village population in an immunisation campaign.She decides to select one village in which health education sessions onimmunisation will be given and another village which will not receiveimmunisation will be given and another village which will not receivehealth education and serves as a control. The immunisation campaignwill be carried out in the same manner in both villages. A survey willthen be undertaken to determine if the immunisation coverage in thevillage where health education was introduced before the campaign issignificantly different from the coverage in the control village which didnot receive health education.

• Note: The study is quasi-experimental because the subjects were not• Note: The study is quasi-experimental because the subjects were notassigned to the control or experimental groups on a random basis.

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What are validity and reliability in research findings?

• Validity means that your scientific observationsactually measure what they intend to measure(your conclusions are true).

• Reliability means that someone else using the samemethod in the same circumstances should be ableto obtain the same findings (your findings arerepeatable).

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• Reliability (repeatability) refers to thepossibility to replicate (repeat) theobservations and is related to the precisionof the instrument used for scientificobservations.

• Validity refers to the soundness of theobservations and to the accurateness of theobservations and to the accurateness of thedata collected by the researchmethod/instrument.

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1. Neither valid nor reliable. The research methods do not hit the heart of the research aim (not valid) and repeated attempts are unfocussed

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2. Reliable but not valid. The research methods do not hit the heart of the research aim, but repeated attempts get almost the same (but wrong) results

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3. Fairly valid but not very reliable. The researchmethods hit the aim of the study fairly closely, butrepeated attempts have very scattered results (notreliable)

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4. Valid and reliable. The research methods hit theheart of the research aim, and repeated attempts allhit in the heart (similar results)

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Sampling

What is sampling?

• Sampling is the process involving theselection of a finite number of elements froma given population of interest, for purposesof inquiry.of inquiry.

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What is a sample?

• A sample is a representative part of apopulation.population.

• A decision is often made, therefore, to studyonly a small fraction of the population, or a“sample” of it, from which conclusions can be“sample” of it, from which conclusions can bedrawn about the whole population.

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What are the characteristics a sampleshould possess?

• A sample should possess all thecharacteristics of the population from whichcharacteristics of the population from whichit is drawn, if possible, so that is fullyrepresentative of the population.

• The method of sample selection usually• The method of sample selection usuallydetermines its representative nature.

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• Several reasons make sampling more usefulthan complete enumeration.than complete enumeration.

• These include considerations regarding:– Time– Costs and available resources, and– Practicability.– Practicability.

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Sampling methods

a) Non-probability sampling methods

1. Convenience sampling: is a method inwhich for convenience sake the study unitsthat happen to be available at the time ofdata collection are selected.data collection are selected.

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Sampling methods

2. Quota sampling: is a method that insures that acertain number of sample units from differentcertain number of sample units from differentcategories with specific characteristics appear in thesample so that all these characteristics arerepresented.

In this method the investigator interviews as manyIn this method the investigator interviews as manypeople in each category of study unit as he can finduntil he has filled his quota.

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Sampling methods3. Purposeful sampling strategies for qualitative

studies:

• Qualitative research methods are typically used when focusing on a limited number of informants, whom we select strategically so that their in-depth information will give optimal insight into an issue about which little is known. about which little is known.

• The above sampling methods do not claim to be representative of the entire population.

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Sampling methodsRandom sampling strategies to collect quantitative data:

• If the aim of a study is to measure variablesdistributed in a population (e.g., diseases) or totest hypotheses about which factors arecontributing significantly to a certain problem,we have to be sure that we can generalise thewe have to be sure that we can generalise thefindings obtained from a sample to the totalstudy population.

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Sampling methods

• Then, purposeful sampling methods are

inadequate, and probability or random

sampling methods have to be used.

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Sampling methods

b) Probability sampling methods:

• They involve random selection procedures to• They involve random selection procedures toensure that each unit of the sample is chosen onthe basis of chance.

• All units of the study population should have anequal or at least a known chance of being includedequal or at least a known chance of being includedin the sample.

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Sampling methods1. Simple Random Sampling (SRS):This is the most basic

scheme of random sampling.

• To select a simple random sample you need to:

– Make a numbered list of all the units in the population from which you want to draw a sample.

– Each unit on the list should be numbered in sequence from 1 to N (Where N is the Size of the population).from 1 to N (Where N is the Size of the population).

– Decide on the size of the sample

– Select the required number of sampling units, using a “lottery” method or a table of random numbers.

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Sampling methods

2. Systematic Sampling:

• Individuals are chosen at regular intervals (for • Individuals are chosen at regular intervals (for example, every 5th, 10th, etc.) from the sampling frame.

• Ideally we randomly select a number to tell us where to start selecting individuals from the list. where to start selecting individuals from the list.

• For example, a systematic sample is to be selected from 1000 students of a school. The sample size is decided to be 100.

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Sampling methods• The sampling fraction is: 100/1000 = 1/10.

• The number of the first student to be included in the • The number of the first student to be included in the sample is chosen randomly by picking one out of the first ten pieces of paper, numbered 1 to 10.

• If number 5 is picked, every tenth student will be included in the sample, starting with student number 5, until 100 students are selected. 5, until 100 students are selected.

• Students with the following numbers will be included in the sample: 5,15, 25, 35,45, . . . , 985, 995.

Hunachew B 190

Sampling methods3. Stratified sampling

• If it is important that the sample includesIf it is important that the sample includesrepresentative groups of study units with specificcharacteristics

– for example, residents from urban and rural areas, thenthe sampling frame must be divided into groups, orstrata, according to these characteristics.

• Random or systematic samples of a predetermined• Random or systematic samples of a predeterminedsize will then have to be obtained from each group(stratum).

Hunachew B 191

Sampling methods4. Cluster sampling:

• When a list of groupings of study units is available • When a list of groupings of study units is available (e.g. villages, etc.) or can be easily compiled, a number of these groupings can be randomly selected.

• The selection of groups of study units (clusters) instead of the selection of study units individually is instead of the selection of study units individually is called cluster sampling.

• Clusters are often geographic units (e.g. districts, villages) or organizational units (e.g. clinics).

Hunachew B 192

Sampling methods5. Multi-Stage Sampling:

• This method is appropriate when the population is • This method is appropriate when the population is large and widely scattered.

• The number of stages of sampling is the number of times a sampling procedure is carried out.

• The primary sampling unit is the sampling unit (or unit of selection in the sampling procedure) in the unit of selection in the sampling procedure) in the first sampling stage;

Hunachew B 193

Sampling methods• The secondary sampling unit is the sampling unit in

the second sampling stage, etc.

• e.g. After selection of a sample of clusters (e.g. household), further sampling of individuals may be carried out within each household selected.

• This constitutes two stage sampling, with the PSU being households and the SSU being individuals.being households and the SSU being individuals.

Hunachew B 194

• The nature of your research study willdetermine which type of sampling you shoulduse.– Large-scale descriptive studies almost always use– Large-scale descriptive studies almost always use

probability-sampling techniques.– Intervention studies sometimes use probability

sampling but also frequently use non-probabilitysampling.

– Qualitative studies almost always use non-– Qualitative studies almost always use non-probability samples.

195Hunachew B

Sample Size Determination

• Many handbooks contain formulae forestimating sample size because the size ofestimating sample size because the size ofthe sample is one of the most importantdeterminates of the accuracy of surveyestimates.

196Hunachew B

Basic questions that should be askedwhen choosing a sample.

1. How large a sample can you collect?– The best advice that can usually be given to a new– The best advice that can usually be given to a new

researcher is that as large a sample as possibleshould be used.

– The larger the sample the smaller the chance thatthe sample will be markedly different from thepopulation it should represent (Minimize samplingerror).error).

2. What level of budget do you have for the study?– The safest procedure is to select as large as your

fund can support, within reason.197Hunachew B

Basic questions…

3. What is the prevalence of the condition you arestudying?studying?

• If you are studying a condition that appearsquite often in a population, you can take asmaller sample than if the condition is quiterare.

4. What staff are available to gather the sample?4. What staff are available to gather the sample?• Limited human resources may be a constraint on

sample size.

198Hunachew B

Basic questions…

5. How much time do you have for the research?• You can only study a limited number of people in a• You can only study a limited number of people in a

certain time.6. Into how many cells or categories are you going to

divide your data for analytical purposes?• The more categories planned for analysis, the larger the

sample must be.sample must be.7. What is the general rule concerning minimum sample

size?

199Hunachew B

Sample size…

• It is generally recommended that a sample size• It is generally recommended that a sample sizeof at least 10, or preferably 20 to 30, be selectedfor each sub-part of data or cell of the designthat will be analyzed.

• A smaller sample can be used if the population• A smaller sample can be used if the populationis relatively homogenous

200Hunachew B

Notice

• Finalized version of your research topic• Group members• Group members• send it to me at: [email protected]• +251911833015

Hunachew B 201

Definitions

• Target population (reference population): Is thatpopulation about which an investigator wishes todraw a conclusion.

• Study population (population sampled): Populationfrom which the sample actually was drawn and aboutwhich a conclusion can be made.

• For Practical reasons the study population is oftenmore limited than the target population.more limited than the target population.

• In some instances, the target population and thepopulation sampled are identical.

Hunachew B. 202

• Sampling unit: The unit of selection in the samplingprocess.

• For example, in a sample of districts, the samplingunit is a district; in a sample of persons, a person,unit is a district; in a sample of persons, a person,etc.

• Study unit: The unit on which the observations willbe collected. For example, persons in a study ofdisease prevalence, or households, in a study offamily size.family size.

• N.B. The sampling unit is not necessarily the sameas the study unit.

Hunachew B. 203

• Sample design: The scheme for selecting thesampling units from the study population.

• Sampling frame: The list of units from which thesample is to be selected.sample is to be selected.

• The existence of an adequate and up-to-datesampling frame often defines the study population.

Hunachew B. 204

In order to calculate the required sample size, thefollowing facts need to be known:

a) The reasonable estimate of the key proportion toa) The reasonable estimate of the key proportion tobe studied.

If you cannot guess the proportion, take it as 50%.

b) The degree of accuracy required.

- the allowed deviation from the true proportion in- the allowed deviation from the true proportion inthe population as a whole.

• It can be within 1% or 5%, etc.

Hunachew B. 205

c) The confidence level required, usually specified as95%.

d) The size of the population that the sample is torepresent.represent.

e) The difference between the two sub-groups and thevalue of the likelihood or the power that helps infinding a statistically significant difference.

Hunachew B. 206

Estimating a proportion

• Estimate how big the proportion might be (P)

• Choose the margin of error you will allow in the • Choose the margin of error you will allow in the estimate of the proportion (say ± w)

• Choose the level of confidence that the proportion in the whole population is indeed between (p-w) and (p+w). and (p+w).

• We can never be 100% sure.

• Do you want to be 95% sure?

Hunachew B. 207

The minimum sample size required, for a very large population (N>10,000) is:

Sample Size to Estimate a Single Population Proportion

The minimum sample size required, for a population (N<10,000) is:

Hunachew B. 208

• Example 1 (Prevalence of diarrhoea)

a) p = 0.26 , w = 0.03 , Z = 1.96 ( i.e., for a 95% C.I.)C.I.)

• Thus, the study should include at least 822 • Thus, the study should include at least 822 subjects.

Hunachew B. 209

• Example 1 (Prevalence of diarrhoea)

a) p = 0.26 , w = 0.03 , Z = 1.96 ( i.e., for a 95% C.I.)C.I.)

• Thus, the study should include at least 822 • Thus, the study should include at least 822 subjects.

Hunachew B 210

b. If the above sample is to be taken from a relatively small population (say N = 3000), the required minimum sample will be obtained from the above minimum sample will be obtained from the above estimate by making some adjustment.

821.25 / (1+ (821.25/3000)) = 644.7 ≈ 645 subjects

Hunachew B 211

• Example 2

• A hospital administrator wishes to know what proportion of discharged patients are unhappy with the care received during hospitalization. If 95% the care received during hospitalization. If 95% Confidence interval is desired to estimate the proportion within 5%, how large a sample should be drawn?

n = Z2 p(1-p)/w2 =(1.96)2(.5×.5)/(.05)2 =384.2 ≈ 385 patientspatients

• N.B. If you don’t have any information about P, take it as 50% and get the maximum value of PQ which is 1/4 (i.e., 25%).

Hunachew B 212

Plan for data collection

• A plan for data collection should be developed so that:developed so that:

– you will have a clear overview of what tasks have to be carried out, who should perform them, and the duration of these tasks;

Hunachew B. 213

– you can organise both human and material resources for data collection in the most efficient way; and.

– you can minimise errors and delays which may result from lack of planning (for example, the population not being available or data forms being misplaced).

Hunachew B. 214

• It is likely that while developing a plan for datacollection you will identify problems (such aslimited manpower), which will require modificationof the proposal.of the proposal.

• Such modifications might include adjustment of thesample size or extension of the period for datacollection.

Hunachew B. 215

• Stages in the Data Collection Process• Three main stages can be distinguished:• Stage 1: Permission to proceed• Stage 1: Permission to proceed• Stage 2: Data collection• Stage 3: Data handling

Hunachew B. 216

Data collection…

• Ideally, a pretest of the data collection anddata analysis procedures should be made.data analysis procedures should be made.

• The advantages of a pretest:-• we can draft the work plan and budget based

on realistic estimates,• revise the data collection tools before we• revise the data collection tools before we

submit the proposal for approval.

217Hunachew B

Points to consider while organizing the data collection team:

• Selection of the candidates• Salary and fringe benefits to be given to the staff (team• Salary and fringe benefits to be given to the staff (team

members)• Training• Planning from the beginning, for possible dropouts• Additional training sessions for new members to fill for

dropouts,dropouts,• What will happen to members hired, at the end of

their work with the project? (Training or certificationfor future jobs, location of future employmentpossibilities)

218Hunachew B

Issues to consider concerning logistics support and arrangements during data collection:

• Mode of transport needed to go to the fieldMode of transport needed when working in the• Mode of transport needed when working in thefield, repairs

• Number of days in the field• Number of days of holiday (personal, weekly and

national) during data collection• Food and lodging for data collection team• Meeting place for the team• Recreational facilities (if needed)

219Hunachew B

Planning for Data analysis

• We need to prepare a plan for analysis of dataand interpretation of the results because itand interpretation of the results because ithelps the researcher avoid becoming aware atthe end of the study, that:– Needed information has not been collected– Certain information collected has not been

analyzedanalyzed– Certain information collected has not been

gathered in a form appropriate for statisticalanalysis

220Hunachew B

• Methods of data collection

• The most commonly used methods of collectinginformation (quantitative data) are the use of

– documentary sources,

– interviews and

– self-administered questionnaires.

Hunachew B. 221

1. The use of documentary sources: Clinicalrecords and other personal records, deathcertificates, published mortality statistics,census publications, etc.census publications, etc.

2. Interviews and self-administeredquestionnaires

Hunachew B. 222

Questionnaire Design

• Questions may take two general forms:

• they may be “Open ended” questions, which the subject answers in his own words, or subject answers in his own words, or

• “closed” questions, which are answered by choosing from a number of fixed alternative responses.

Hunachew B. 223

In questionnaire design remember to:

a) Use familiar and appropriate language

b) Avoid abbreviations, double negatives, etc.

c) Avoid two elements to be collected through one questionc) Avoid two elements to be collected through one question

d) Pre-code the responses to facilitate data processing

e) Avoid embarrassing and painful questions

f) Watch out for ambiguous wording

g) Avoid language that suggests a responseg) Avoid language that suggests a response

h) Start with simpler questions

i) Ask the same question to all respondents

Hunachew B. 224

• Methods of collecting qualitative data– Focus group discussion– Observation

Hunachew B. 225

Plan for data processing and analysis

• Data processing and analysis should start in the field, with checking for completeness of the data field, with checking for completeness of the data and performing quality control checks, while sorting the data by instrument used and by group of informants.

• Data of small samples may even be processed and • Data of small samples may even be processed and analyzed as soon as it is collected.

Hunachew B. 226


• When making a plan for data processing and analysis the following issues should be considered:analysis the following issues should be considered:

– Sorting data,

– Performing quality-control checks,

– Data processing, and

– Data analysis.

Hunachew B. 227


• Data processing in both cases involves:– categorising the data,– categorising the data,– coding, and – summarising the data in data master sheets,

manual compilation without master sheets, or data entry and verification by computer.

Hunachew B. 228

• Data analysis – quantitative data– 1. Frequency counts– 2. Cross-tabulations– 2. Cross-tabulations

• Processing and analysis of qualitative data

Hunachew B. 229

Ethical considerations• Ethical principles Autonomy- we ought to respect the right to self-

determination. In research autonomy is protected bydetermination. In research autonomy is protected byensuring that any consent to participate in the studyis informed or real.

Non-Maleficence- we ought not to inflict evil orharm.

Beneficence – we ought to further others’ legitimate Beneficence – we ought to further others’ legitimateinterests.

Justice-we ought to ensure fair entitlement toresources.

Hunachew B. 230

Work plan

• A work plan is a schedule, chart, or a graphthat summarizes, in a clear fashion, variousthat summarizes, in a clear fashion, variouscomponents of the research project and howthey fit together.

A work plan may include:– The tasks to be performed (activity)– When the tasks will be performed (time)– When the tasks will be performed (time)– Who will perform the tasks and the time each

person will spend on them (person)– The relationship of the tasks to each other.

231Hunachew B

Ways of presenting a work plan

A work plan could be presented in the form of:a work schedule and GANNT charta work schedule and GANNT chart

The Work Schedule• A work schedule is a table that summarizes

the tasks/activities to be performed in theresearch project, the duration of eachresearch project, the duration of eachactivity, and the staff responsible.

232Hunachew B

Work plan…

The work schedule includes:– the tasks to be performed;– the tasks to be performed;– the dates each task should begin and end– research team, research assistants, and support staff

(drivers and typists) assigned to the tasks; and– person-days required by the research team members,

research assistants, and support staff (the number ofperson-days equals the number of working days perperson-days equals the number of working days perperson).

– The work schedule shows the tasks to be completed,how long they take, and who is to be assigned to eachone.

233Hunachew B

234Hunachew B

The GANTT Chart

• The Gantt chart is a planning tool which depictsgraphically the order in which various tasks must becompleted and their duration of activity.completed and their duration of activity.

• A typical Gantt chart includes the followinginformation:

– The tasks to be performed

– Who is responsible for each task; and

– The time each task is expected to take.

235Hunachew B

The GANTT Chart

• The length of each task is shown by a bar that extendsover the number of days, weeks or months the task isexpected to take.expected to take.

• The Gantt chart shows the tasks to be completed andillustrates visually how long they will take.

236Hunachew B

GANNTs Chart

Activities Time in months

January February March April May June

Proposal development (PI)

XXXXXX

Ethical clearance XXXXX

Field work XXXXXField work XXXXX

Data entry XXXXX

Data analysis XXXXX XXXXX

237Hunachew B

Preparation of a budget

There are several reasons why we need a budget:

• A detailed budget will help you to identify whichresources are already locally available and whichadditional resources may be required.

• The process of budget preparation will encourageyou to consider aspects of the work plan you haveyou to consider aspects of the work plan you havenot thought about before and will serve as a usefulreminder of activities planned, as your researchgets underway

238Hunachew B

How should a budget be prepared?

• It is necessary to use the work plan as astarting point. Specify, for each activity in thestarting point. Specify, for each activity in thework plan, what resources are required.

• Determine for each resource needed the unitcost and the total cost.cost and the total cost.

239Hunachew B

Budget justification

• Make sure you give clear explanations concerning whyitems that may seem questionable or that areitems that may seem questionable or that areparticularly costly are needed and discuss howcomplicated expenses have been calculated.

• If a strong budget justification has been prepared, it isless likely that essential items will be cut duringproposal review.proposal review.

240Hunachew B

241Hunachew B

Appendices

• Include in the appendices of your proposalany additional information you think mightany additional information you think mightbe helpful to a proposal reviewer. Forexample, include:

– Biographical data of the principal investigator

– The study questionnaire if you have it.

– The consent form.

242Hunachew B

Appendices– A copy of the approval from the Institutional

Review Board.Review Board.

– Any explanatory material (such as annual report)about your institution or the origination underwhose name the study will be conducted.

– A list of references if you have cited literature inthe proposal.

243Hunachew B

Title page and abstract• Although the title page and abstract appear as the first

section of a research proposal, they are the last to bewritten.written.

• The title page gives the essential information about theproposal. Immediately following the title page you shouldinclude an abstract.

• The abstract is a summary of the basic informationcontained in all the other sections of your proposal.contained in all the other sections of your proposal.

• Do not overload an abstract with unnecessaryinformation. Keep it short (no longer than one or twopages), precise, and to the point.

244Hunachew B

The abstract should tell the reader:

1. The problem to be studied.2. The main objective of the study.2. The main objective of the study.3. The major expected implications of the study.4. Who will conduct the study5. When the study will be conducted.6. Where the study will be conducted.6. Where the study will be conducted.7. What methods will be used to conduct the

study.8. What resources are required for the study.

245Hunachew B

246Hunachew B

assessment of the prevalence of diarrheal disease in addis ababa

By Group members:By Group members:

A resarh proposal submited for partial fulfilment of the degree of medicine, addis ababa

universityuniversity

June 2012

Hunachew B 247

• Summary of the major components of a research proposal– Title and cover page– Abstract– Abstract– Table of contents– I) Introduction– Statement of the research problem– State of knowledge: knowledge pertinent to

subject under studysubject under study– Significance of the proposed work– II) Objective of the study

Hunachew B. 248

III) Materials and methods

• Type of study (study design)

• Study population• Study population– Describe the study areas and populations

– Mapping and numbering of the study area

– Appropriateness of the study

– Accessibility (provide background information, – Accessibility (provide background information, travel, time, etc...)

– Cooperation and stability of the population

Hunachew B. 249

• Type of data (defining each variable to be collected and methods for collecting them

– Operational definitions– Some elements of the variables to be studied:

Hunachew B. 250

• What characteristics will be measured? How will the variables be defined? What scales of measurement will be used etc.– Inclusion/ exclusion criteria– Inclusion/ exclusion criteria

– Sampling procedure to be used and sample size and power calculation.

– Data collection and management

• Data collection and coding forms should be • Data collection and coding forms should be appended to protocol

• Data analysis

Hunachew B. 251

– Management of dropouts

– Frequencies, rates, other parameters

– Statistical programs and tests to be used– Statistical programs and tests to be used

– Data presentation (dummy tables to be appended)

• Ethical considerations: rights and welfare of the subjects and method of obtaining their informed consentconsent

• Pretest or pilot study: (allows us to identify potential problems in the proposed study)

Hunachew B. 252

IV) Work planV) Budget (itemize all direct costs in Ethiopian

Birr)lan (project management)VI) References: List only those cited in text andVI) References: List only those cited in text and

number by order they appear in text usingArabic numerals.

VII) Appendices: -– Data collection and coding forms– Data collection and coding forms

– Dummy tables for data presentation

– Letters of support (cooperation)

Hunachew B. 253

8.3 Writing a research report• Title and cover page• Abstract (Summary)• Acknowledgements• Table of contents• List of tables, figures• List of abbreviations (optional)I) IntroductionI) IntroductionII) ObjectivesIII) Methods

Hunachew B. 254

• The methodology you followed for the collection of your data should be described in detail.detail.

• The methodology section should include a description of:

– the study type;

– major study themes or variables (a more detailed – major study themes or variables (a more detailed list of variables on which data were collected may be annexed);

Hunachew B. 255

– the study population(s), sampling method(s) and the size of the sample(s);

– data-collection techniques used for the different – data-collection techniques used for the different study populations;

– how the data were collected and by whom;

– procedures used for data analysis, including statistical tests (if applicable).statistical tests (if applicable).

Hunachew B. 256

IV) Results• Findings should be presented• Tables and graphs could be used (should be well titled and

captioned)• The tables should be well constructed, and without

anomalies such as percentages which do not add up to 100 percent

• Avoid too many decimal places• Graphs should clarify and not complicate, and care should

be taken that they do not mislead• If appropriate statistical tests are used, the results should

be included. P-values alone are not very helpful. Confidence intervals and the type of tests used should be indicated.

Hunachew B. 257

V) Discussion

• The findings can now be discussed by objective or by cluster of related variables or themes, which should lead to cluster of related variables or themes, which should lead to conclusions and possible recommendations.

• The author interprets the findings. Care should be taken not to introduce new findings, i.e., findings not mentioned in the result section.

• The discussion may include findings from other related • The discussion may include findings from other related studies that support or contradict your own.

• Limitation of the study and generalizability of the finding should also be mentioned.

Hunachew B. 258

VI) Conclusions and recommendations• The conclusions and recommendations should

follow logically from the discussion of the findings. • Conclusions can be short.• Conclusions can be short.• As the discussion will follow the sequence in which

the findings have been presented (which in turn depends on your objectives) the conclusions should logically follow the same order.

Hunachew B. 259

VIII) Annexes or appendices• The annexes should contain any additional

information needed to enable professionals tofollow your research procedures and datafollow your research procedures and dataanalysis.

• Examples of information that can be presentedin annexes are:– tables referred to in the text but not included in

order to keep the report short;order to keep the report short;– lists of hospitals, districts, villages etc. that

participated in the study;– questionnaires or checklists used for data collection.

Hunachew B. 260

261Hunachew B

proposal writing revised

Technology

research questions

research data

types of research

undertaking health research

health research ethics7

health systems research

components of research

characteristics of research