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Table 1 Some examples of purposeful sampling methods [14]

From: Purposive sampling in a qualitative evidence synthesis: a worked example from a synthesis on parental perceptions of vaccination communication

Type of sampling Description
Extreme or deviant case sampling • Selecting illuminative cases that exemplify ‘extreme’ or ‘deviant’ contexts or examples, for instance:
  – where an innovation in a primary study was perceived notably as a success or failure
  – where findings of a primary study are very different from those of most studies identified for the synthesis
Maximum variation sampling • Constructed by:
  – identifying key dimensions of variation, and then
  – finding cases that vary from each other as much as possible along these dimensions
• This sampling yields:
  – ‘high-quality, detailed descriptions of each case, which are useful for documenting uniqueness, and
  – important shared patterns that cut across cases and derive their significance from having emerged out of heterogeneity’ (Patton, 2002, p. 235)
Snowball or chain sampling • Trying to locate a key work in the field through talking with experts or locating a key article that is often cited
• Then follow on with primary studies that have cited the key or landmark study
Theoretical or operational construct sampling • Selecting cases that represent important theoretical or operational constructs about the phenomenon of interest
• Set out operational definitions of key theories or constructs related to the phenomenon of interest
• Develop boundaries for these by creating specific inclusion and exclusion criteria in relation to selecting primary studies for the synthesis
Criterion sampling • Used by those trying to construct a comprehensive understanding
• Studies are sampled based on a predetermined criteria
• Specific inclusion and exclusion criteria are clearly stated
• Studies are then analysed as a whole
Stratified purposeful sampling • Following on from criterion sampling where each of the criteria would become a sample
• Stratified samples are samples within samples where each stratum, or group, is fairly homogenous and are analysed within these groups
• Useful for examining variation in a key phenomena of interest
Purposeful random sampling • Randomly select from the list of included studies for inclusion in the analysis
• For example, use a random internet based selector, choose every 3rd included study or pull study names from a hat
• Provides an unbiased way of selecting studies for inclusion but may not provide studies with rich data
Combination or mixed purposeful sampling • Choosing a combination or mix of sampling strategies to best fit your purpose
  – For some syntheses, it may be useful to use a combination or mix of sampling strategies. For instance, by applying theoretical sampling in a first stage and deviant case sampling in a second stage. This should be guided by the review methods and purpose, and the time available