Presentation on theme: "From analysis plan to data collection Helen Maguire acknowledgements Katharina Alpers, Yvan Hutin."— Presentation transcript:
from analysis plan to data collection Helen Maguire acknowledgements Katharina Alpers, Yvan Hutin
its logical: data collection follows the analysis plan.. Research question: ? Risk factors for leptospirosis Study objectives: Estimate association between water exposure and disease Design/ indicator: Case control Odds ratio Analysis plan: Dummy table Data elements Needed: ? Water exposure ? Sick Data collection: Interview Individual items: ? Swam in water ? Sick Consolidation of the instrument
data quality reliability accuracy Data quality
data quality reliability –reproducibility/repeatability/precision –ability of a measurement to give the same result or similar result with repeated measurements of the same thing –refers to stability or consistency of information accuracy ability of a measurement to be correct on the average Data quality
reliability and accuracy Data quality
Reliable Accurate Not reliable Accurate Reliable Not accurate Not reliable Not accurate reliability and accuracy Data quality
some essentials 1.question-by-question guide 2.train staff who collect data 3.standardize the data collection procedure 4.control instruments or specimen collection 5.validate Data collection
1 question by question guide (q-by-q) short document each question/data item – item by item guidance as to how the data should be collected derived variables explained Data collection
2 train field workers select good, experienced field workers walk through q-by-q guide explain where data is clarify how to record it simulate interviews with team Data collection
3 standardize data collection interviewers –work in teams –resolve issues in the whole group instruments/specimens/samples –calibration, standardization, packaging, media, transport Data collection
4 control instruments team checks instrument/samples before leaving all take responsibility for the instrument: –names and signatures investigator checks instruments/samples as they come Data collection
5 validate how would you validate/verify?
example - triangulation to estimate the proportion of blood units screened for HIV (internal validation) interview laboratory manager ? what is the number of units screened observe practices of the laboratory technician –structured observation guide ? proportion of units tested review of registers - ? a sample –proforma ? number of tests ordered, performed Instruments
data might include facts –individual characteristics height, age, income –environment housing, family size –behaviours, practices alcohol or tobacco consumption judgements – attitudes/opinions indicators of socio-economic status … blood test results environmental samples Instruments
list some ways to collect data Instruments
proformas –clinical records –surveillance records –registers questionnaires sampling /laboratory results other data –socio-economic status derived from postcode –via linkages –denominator data –reference data
checking the instrument(s) against the analysis plan make sure you can collect what you need for each variable /indicator suppress unnecessary data collection or questions at interview –those that do not be used in the analysis Production of the instrument
is a questionnaire good? why? list 5 advantages and 5 disadvantages
advantages of questionnaires can reach a large number of people relatively easy and economic relate directly to study question provide quantifiable answers relatively easy to analyse
possible disadvantage of questionnaire bias …? how might it be introduced at this stage? how would you avoid it? pilot - check for leading questions
how to reduce bias structured questionnaire ensure high response rate random choice of interview partners (next birthday) train interviewers
disadvantages of questionnaires provide only limited insight into a problem –the range of possible responses is limited –the question maybe misleading Unclear question can lead to misunderstanding misinterpretation do not allow for mistakes –must be right from the beginning –missing data hard to chase how to avoid ?
pilot testing of the questionnaire check that the questionnaire is: –clear –understandable –acceptable check flow and skip pattern check coding estimate time needed Production of the instrument
how would you administer a questionnaire?
questionnaires internet/ /post self completion interviewer- administered –face to face –telephone
what makes a well designed questionnaire?
good appearance (easy for the eye) short and simple numbering / flow /sign-posting /instructions/where to return and how relevant and logical
introduction covering letter/ interview introduction –Who are you / you work for –Why are you investigating –Where did you obtain the respondents name –How and where can you be contacted –Guarantee of confidentiality –Length of interview (be honest) Usefulness of study should be clear to all respondents
Good morning, My name is Katharina Alpers...., I work for …….. You may have been already informed that a survey on risk factors for being stung by a jellyfish will be done this week in Mahon. This study has been approved by the Spanish national ethical committee. Only anonymous data will be analysed. You have been randomly selected to participate in this study. Your participation is voluntary. The interview is about 10 minutes long. Are you able to help us? thanks so much.....
questions do you like to go swimming and do you mind being stung by jellyfish? Yes No
what is the jellyfish situation? Good Bad versus how often did you see jellyfish during the last week? Once Twice Three times or more Never Don´t know
did you see more than an average of 33 jellyfish/m 2 salt water surface on more than 3 occasions that you went swimming in the morning last week? Yes No versus have you seen jellyfish on more than 3 mornings last week? Yes No Don´t know
main question formats closed format forced choice Yes Always No Sometimes Dont know Never open format free text What did you do to avoid being stung by jellyfish? Please describe : __________________________________________ ________________________________________
when would open questions be good ? what problems might there be with open questions?
advantages of open questions exploration possible – to generate hypotheses useful for exploring knowledge and attitudes qualitative research focus groups trawling questionnaires
disadvantages of open questions interviewer bias time-consuming coding problems difficult to analyse difficult to compare groups
advantages of closed questions simple less discrimination against less verbally expressive people easy to code, record, analyse easy to compare
disadvantages of closed questions restricted number of possible answers possible loss of additional information Compromise if yes specify : __________
which of the following beaches have you visited during your stay in Menorca? Lazareto beach Yes No Don´t know Calan Porter Yes No Don´t know Rafalet Yes No Don´t know Macarella Yes No Don´t know Sa Mesquida Yes No Don´t know checklist
rating scale how often did you see jellyfish during the past week? Always Sometimes Seldom Never Mornings Lunchtime Evenings
rating scale numerical how severe was your pain after you were stung? (please circle) Not painful at all Very painful analogue how severe is your pain (put the tick on the line) 010
Likert Scale Rensis Likert, Five (or more) ordered response levels Jellyfish also have the right to swim in the Mediterranean sea I strongly disagree I disagree I neither agree or disagree I agree I strongly agree
problems and pitfalls avoid questions that ask two things at once - you wont know which part people are answering: have you seen or been stung by jellyfish? ambiguity..... do you swim a lot?
problems and pitfalls avoid jargon/abbreviations/slang should jellyfish sting victims receive PEP? (post exposure prophylaxis) avoid not mutually exclusive options What is your age ?
summary a well designed questionnaire: helps you answer your research question minimises potential sources of bias -> increases the validity of the replies is more likely be completed
questionnaire validation use or adapt existing questionnaires –validated new questionnaires –need to be tested (pilot)
conclusion dont forget to thank the interviewed persons tell them when the results will be available and where
take home messages think instruments, data sources, not only questionnaire list your indicators prepare your variables ->indicators prepare dummy tables polish, polish and polish to ensure good data quality