Mother and Child Health: Research Methods

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Mother and Child Health Research Methods

• G.J.Ebrahim
• Editor
• Journal of Tropical Pediatrics, Oxford University
  Press.

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Bias

• Bias means different
• 3 types of bias
• Selection Bias
• Information Bias
• Confounding

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Selection BiasExamples

• Patients referred for specialist care are
  different from those in the community
• Migration bias. People with chronic lung disease
  tend to move out of urban areas those with
  psychiatric problems seek the anonymity of cities
• High dropout rates. Those who drop out of a study
  tend to be different from those continuing

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Information BiasExamples

• Response Bias occurs when subjects give
  inaccurate responses.
• Measurement Bias occurs when instruments are
  faulty
• Observer error
• A process tends to show improvement when being
  observed. (Hawthorne Effect)

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Strategies for Avoiding Bias

• Have clear and precise definitions (e.g. for
  cases controlsexposurecriteria for
  inclusion/exclusion)
• Blinding where appropriate
• Reduce measurement error by quality control
• careful check of study design choice of
  subjects ascertainment of disease and
  exposureplanning of questionnaires methods of
  data collection.

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Confounders

• Confounders act by being associated with both a
  risk factor and outcome in a way that makes the
  two seem related.

Poor Maternal Nutrition
Low Birth Weight
Low Socioeconomic Class
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Dealing with Confounders - 1

• Think about possible confounders at the design
  stage, and gather data on all possible
  confounders.
• A quick test about a possible confounder is to
  check whether it is unevenly distributed between
  study and comparison groups.
• Suspect confounding if the odds ratio gets
  altered after adjusting for another factor.

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Method of Checking for a Possible Confounder

• First calculate Odds Ratio for the exposure
  variable.
• Next calculate odds ratio for different strata
  of the confounding variable
• If the odds ratios are not materially different
  then there is no confounding.

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Strategies for dealing with Confounding

• Design Stage
• Strict inclusion criteria
• Matching
• Randomization
• Analysis Stage
• Do analysis by adjusting for several strata of
  the confounding variable
• Multiple regression analysis

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Validity

• Are the conclusions true?
• Common threats to validity
• Selection bias
• Measurement bias
• Differential loss of subjects
• Confounders
• Unexpected events
• Hawthorne effect

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Strategies for ensuring validity

• Have a control group. Helps against
  confounding, unexpected events, Hawthorne
  effect.
• Random assignment of subjects to different
  groups.
• Before / After measurements.
• Carefully prepared research designs.
• Quality control of equipment
• Knowledge of environmental events especially if
  the study is of long duration.
• Unobtrusive methods of observation.