data collection part 3 of 4 Flashcards
what are the 2 different types of studies which need to be considered when deciding the type of data collection
prospective
retrospective
define prospective study
record variables over the the study period with the outcome measure subsequently.
define retrospective study
measure the outcome and then look bad to measure the exposure and other variables.
An example of a prospective study
cohort
An example of retrospective study
case control study
cross sectional study
what are the pros of a prospective study
- fewer sources of bias (no recall bias)
- less chance of confounding
- some data can only be measure prospectively
what are the cons of a prospective study
- time and resource intensive
- tendency to collect data on more variables than you need or can use in your analyses.
- subjects can drop out (bias)
- unfeasible for rare outcomes
what are the pros of a retrospective study
- less time and resource intensive
- allows oversampling of rare outcomes
what are the cons of retrospective study
- more suitable to bias (recall + recruitment)
- some variable cannot be measure directly (e.g. BMI, BP, pre outcome/ pre treatment)
- if data are form records little control over these
what is the purpose of a research diary
- ensure timely record of what you do
- observations on data collection processes influencing data quality and completeness.
what id the purpose of a data collection pro forma
-variables are measures and recorded CONSITENTLTY.
What is a commonly used pro forma
questionnaire
what are 3 common pit falls in questionnaires
- ambitigious questions (would you normally feel uncomfortable about your diabetes.
- leading questions ( to what ethnic group do you belong
- multiple questions (have you found diabetes to be limiting longstanding illness)
what are 2 types of questions used in a questionnaire
- open ended (respondent determined)- need coding prior to analysis
- closed ended (part respondent/part researcher determined)
what does piloting proformas mean
Ask non-participants/researchers to try using draft versions of the questionnaires/proformas – are they:
- ambiguous?
- leading?
- multi-factored?
- undermined by missing answer categories?
- ‘face valid’ (i.e. do they make sense)?
Try ‘coding’ and/or capturing data from a sample of completed questionnaires/proformas – are there:
- missing answers?
- inconsistent answers?
- implausible answers?