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Table 2 Q-methodology results

From: Appraising patient preference methods for decision-making in the medical product lifecycle: an empirical comparison

Most important criteriaA: Early developmentB: Early developmentC: Late phase IIID: Post-marketing
A typical survey can be conducted at relatively low costs  
Data can be collected during quick sessions with participants  
Low frequency of sessions required by patients 
Relatively quick delivery of preparation, data collection, and analysis
A large number of attributes can be explored   
Suitable to study preferences in a small sample size 
A low cognitive load on patients
Does not need an education tool or preparatory instructions in order to enhance participant comprehension  
Publically acknowledged by your organisation’s guidelines as an acceptable method to study preferences  
New attributes can be added without making prior results invalid 
Can be used to collect data from more than one participant in a single session   
The analysis can calculate risk attitudes, like risk tolerance, and calculate how value functions bend due to the presence of uncertainty in the participant
Explores the reasons behind a preference in detail
Can estimate weights for attributes
Estimates trade-offs that patients are willing to make among attributes
Can quantify heterogeneity in preferences
Internal validity can be established
External validity can be established
Outcomes can refer to a course of health over time (as opposed to a constant health state)  
Sensitivity analysis is possible
Can combine quantitative and qualitative methods 
Applies validation tests 
Results can be reproduced by an (independent) researcher for reproducibility
Applies tests for consistency  
Can be conducted without the need for specialized software (beyond Excel)    
Can be conducted without programming skills    
Researcher does not need to supervise the data collection    
Does not require hypothetical scenarios    
Attributes and attribute levels can be determined as part of the method itself (internal identification)    
Data saturation can be achieved relatively quickly    
Does not require model estimations    
Outcomes can be expressed in a particular format (e.g. probability scores, marginal rates of substitution, monetary values)    
Outcomes can refer to a constant health state (as opposed to a course of health over time)    
Uses respondent validation by asking participants to check their data or responses    
Validates through triangulation    
  1. Criteria considered important in the Q-methodology, included in the AHP
  2. ✘ Criteria considered important in the Q-methodology, but not included in the AHP for the following reasons: 1. The criterion does not sufficiently discriminate between each method (i.e. every method would perform the same way under the criterion), 2. The criterion reflects an element of good study conduct, and not a unique aspect of a method itself, 3. The criterion could be absorbed into other similar criteria, in order to avoid the oversaturation of themes