going after the data data collection instruments fetp india

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Going after the data Data collection instruments FETP India

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Going after the data

Data collection instruments

FETP India

Competency to be gained from this lecture

Design effective data collection instruments

Key elements

• Instruments• Items• Finalization

The data collection instrument is a logical deduction of the analysis plan

Research question:? Risk factors for

leptospirosis

Study objectives:Estimate association

between water exposure and

disease

Design/ indicator:Case controlOdds ratio

Analysis plan:Dummy table

Data elementsNeeded:

? Water exposure? Sick

Data collection:Interview

Individual items:? Swam in water

? Sick

Consolidationof the

instrument

Information that may be collected with a data collection instrument

• Facts• Judgements• Indicators of knowledge

Instruments

Information that may be collected with a data collection instrument

• Facts Individual characteristics

• Height, age, income

Environment • Housing, family size

Behaviours, practices• Alcohol or tobacco consumption

• Judgements• Indicators of knowledge

Instruments

Information that may be collected with a data collection instrument

• Facts• Judgements

Opinions Attitudes

• Indicators of knowledge

Instruments

Information that may be collected with a data collection instrument

• Facts• Judgements• Indicators of knowledge

Risk factors Elements of healthy lifestyle

Instruments

Classical way to explore behaviours and their determinants in

epidemiology• Knowledge • Attitude• Practices

Instruments

Different ways to collect data with an instrument

• Abstraction form Clinical records Surveillance records Registers

• Structured observation guide• Questionnaire

Instruments

Triangulation to reconstitute the best possible reflection of the truth

• Collection of information on the same topic through various mechanisms

• Attempt to reconstitute a reliable reflection of the parameter

Instruments

Examples of triangulation to estimate the proportion of blood

units screened for HIV

• Interview of the laboratory manager Questionnaire

• ? What is the number of units screened

• Observation of the practices of the laboratory technician Structured observation guide

• ? Proportion of units tested

• Review of registers Abstraction form

• ? Number of tests ordered, used

Instruments

The four components of a data collection instrument

• Introduction and conclusion• Identifiers • Instructions for the person who collects

data• Body of the instrument

Items

The four components of a data collection instrument

• Introduction and conclusion Introduction

• Presentation, objectives• Elements needed for

informed consent Conclusion

• Identifiers • Instructions for the person who collects

data• Body of the instrument

Items

The four components of a data collection instrument

• Introduction and conclusion• Identifiers

Exact identifiers (e.g., name, address)• Collect and keep apart • Not entered in the computer

Coded ID number (composite)• Entered in the computer

• Instructions for the person who collects data

• Body of the instrument

Cluster

House

Person

Items

The four components of a data collection instrument

• Introduction and conclusion• Identifiers • Instructions for the person who collects

data Guide for the person who collects data Instructions (e.g., prompts) Skip patterns Use different fonts (e.g., italics)

• Body of the instrument

Items

The four components of a data collection instrument

• Introduction and conclusion• Identifiers • Instructions for the person who collects

data• Body of the instrument

Open items Closed items Semi-open items

Items

Different types of items in the body of a questionnaire

• Open questions The interviewer leaves the answer free

• Closed questions The interviewer proposes options of answers

• Semi-open questions The interviewer proposes options of

answers, but additional free answers are possible

Items

Open questions

• Answers are not suggested • Subjects must generate an answer• Advantages

Give freedom of response Stimulate memory Can be useful to generate closed responses later Useful at a hypothesis raising stage

• Inconvenient Difficult to code and analyze May be incomplete and / or unfocused

Items

Examples of open questions

• What disease can you acquire from tobacco?

• What places did you eat at in the week preceding the disease?

Items

Open questions with close ended answers

• No option of answer is suggested• However, among the answers freely

mentioned, the interviewer will tick those spontaneously specified

• Expressed as an open question • Analyzed as a close-ended question

Items

Example of open question with close ended answers

• What are the practices that may increase your risk to get a heart attack? (DO NOT propose any option of answer) Lack of exercise (Yes/No) Smoking (Yes/No) Poor dietary practices (Yes/No) Eating too much salt (Yes/No)

Items

Closed questions:1. Dichotomous options

• Suggested answers include “Yes” and “no”

• Advantages Forces a clear position May be useful for key, important, well

framed issues

• Inconvenient May oversimplifies issues

Items

Good and bad examples of closed dichotomous questions

• Have you ever consumed tobacco products? A dichotomous question here is likely to

over-simplify, unless it is used as an introduction

• Did you eat at restaurant X between 1 and 28 February?Adapted to an outbreak investigation

Items

Closed questions:2. Multiple options

• Multiple options of answers are suggested

• Advantage Larger choice of answer options

• Inconvenient May be difficult to choose only one option

Items

Examples of closed questions with multiple options

• Where do you go to seek treatment when moderately sick? (e.g., for fever) Hospital Public clinic Private clinic Pharmacist

• Do you wear a helmet when riding a bike? Always Sometimes Never

Items

Differentiating questions with multiple options from multiple

dichotomous questions • If more than one option of response, be

clear as to whether one or multiple answers are acceptable

• Only one answer acceptable=One variable with multiple options

• More than one answer acceptable=Equivalent to multiple dichotomous

variables

Items

Example of question with multiple options that lead to ambiguities

• What are the elements that led you to stop smoking? ? Fear of the danger of tobacco? Diagnosis of a tobacco related illness? Fear of dependence? Cost of tobacco products

• Two possibilities: Accept only one answer Accept multiple answers

Items

Possibility 1: More than one option acceptable

• What are the elements that led you to stop smoking? Fear of the danger of tobacco Diagnosis of a tobacco related illness Fear of dependenceCost of tobacco products

=Equivalent to multiple dichotomous questions, each option being a variable

Items

Clarified possibility 1: More than one option acceptable

• Among these elements, what are those that led you to stop smoking? Fear of the danger of tobacco

• Yes / No Diagnosis of a tobacco related illness

• Yes / No Fear of dependence

• Yes / No Cost of tobacco product

• Yes / No

Items

Possibility 2: Only than one option acceptable

• What are the elements that led you to stop smoking? Fear of the danger of tobacco Diagnosis of a tobacco related illness Fear of dependence Cost of tobacco products

=Equivalent to one question with multiple options of answers, one variable

Items

Clarified possibility 2: Only than one option acceptable

• Among these elements, what is the one that was most important in your decision to stop smoking? Fear of the danger of tobacco Diagnosis of a tobacco related illness Fear of dependence Cost of tobacco products

Items

Closed questions:3. Quantitative answers

• The subject must provide a quantified answer

• Advantage Allows creation of continuous variables

• Inconvenient May requires validation:

• Some “quantified” answers might be limited in the way they can be handled as continuous variables

Items

Example of closed questions with quantitative answers

• How many time did you visit the clinic in the last 12 months? True continuous variable Four visits is the double of two visits

• How would you describe your pain on a 1-10 scale where 1 would be the minimum and 10 would be the maximum? In fact a qualitative variable with 10 options Requires validation

• Six may not be the double of three on the scale

Items

Semi-open questions

• Suggested answers • Possibility to create another answer

Other, specify: __________

• Advantage Leaves the door open to unplanned answers

• Inconvenient Difficult to analyze

Items

Examples of semi-open questions

• Did you child have complication following measles? None Pneumonia Diarrhoea Eye problems Other, specify: ______________

Items

Formulating questions (1/2)

• Write short and precise questions Avoid ambiguities

• Use simple words of every day language• Avoid negations and double negations

Do you sometimes care for patients without washing hands?

Do you systematically wash hands before caring for each patient?

Production of the instrument

Formulating questions (2/2)

• Ask only one question at the time Did you refuse treatment because you feared side

effects? Did you refuse treatment? If yes, was this because you feared side effects?

• Be specific Are you aware of the modes of transmission of HIV? Among these practices, can you tell me those that

could lead to HIV?

• Use neutral tone to avoid influence Have you been promiscuous in the last six months? How many partners have you had in the last six

months?Production of the instrument

Sorting questions

• From the general to the specific • From the simple to the complicated• From the casual to the intimate• Regroup identification questions at the

beginning or at the end• Introduce simple questions as a break if

the questionnaire is complex• Triangulate through multiple questions

on the same topic if the subject is important

Production of the instrument

Careful lay out the data collection instrument: Rationale

• Easier to use• Guides the field worker• Reduces the risk of errors• Reduces the risk of forgotten questions• Simplifies coding • Simplifies data entry

Production of the instrument

Careful laying out the data collection instrument: Principles

• Split the sections• Space out questions• Use larger fonts• Align answers on the right hand side• Do not split questions across pages• Number questions• Standardize coding • Use auto-coding procedures

Production of the instrument

Auto-coding

• Q.25: Where did you go when your child had diarrhoea? 1. Hospital2. Public clinic3. Private clinic4. Pharmacist

2

Production of the instrument

Checking the instrument against the analysis plan

• Suppress unnecessary questions Those that do not be used in the analysis

• Add missing questions Those that will provide variables needed in

the analysis

Production of the instrument

Colleagues who can help in reviewing the questionnaire

• Colleagues• Experts• Statisticians (Coding)• Field workers • Data entry clerks

Production of the instrument

Language

• All questionnaires must be written in the language in which they will be administered Not acceptable to have an English questionnaire

translated in the field by the interviewers• No standardization

• Translation is required, with quality assurance Initial formulation (e.g., in English) Translation (e.g., in Hindi) Back-translation (e.g., back to English)

Production of the instrument

Objectives of the pilot testing of the questionnaire

• Check that the questionnaire is: Clear Understandable Acceptable

• Check flow and skip pattern• Check pertinence of coding • Estimate the time needed to ask all the

questions

Production of the instrument

Pilot testing the questionnaire in practice

• Pilot test with yourself • Pilot test with a few volunteers • Pilot test in real size

Persons similar to the study population Persons who are not to be included in the

study

Production of the instrument

Producing the last version of the questionnaire

• Professional finish• Paper of good quality• Interviewer’s kit

Sleeves Clip board Pencil, eraser

Production of the instrument

Summary of the systematic process leading to the data collection

instrument

Research question

Study objectives

Design/Indicators

Analysis plan

Data elementsneeded

Choice of data

collectionmethod

Formulation of individual

items

Consolidationof the

instrument

DANGER: By pass leads to poor studies

Take home messages

• Think instruments, not only questionnaire

• Prepare your items as future variables• Polish, polish and polish to ensure good

data quality

Additional resources on data collection instruments

• Case study on protocol writing (Scrub Typhus in Darjeeling, Volume 2)

• Example of questionnaire• Guide to common errors in data

collection instruments (with checklist)