Phenomenological studies, particularly those utilizing closed-ended questionnaires in qualitative research, are gaining increasing attention. However, they often face challenges in establishing robust statistical inferences, as they depend on the respondents’ honesty and are affected by bias and measurement variability between different types of responses within a given domain. RS score accurately estimates a latent variable when all responses/items of the domain are of the same scale, but not valid when responses of a domain are of different scales. Hence, this study examines the challenges of using closed-ended responses in qualitative research and highlights strategies for mitigating bias and measurement variations in responses of different scales in a domain in the form of an IAR score. To capture the qualitative degrees of participants’ experiences in response to a range of types of responses/items within a specific domain, a standardized approach was employed to assign integer values to responses, ensuring balanced weighting and comparability. This method helps to mitigate bias and measurement variability within and between items by averaging each response as a proportion of its highest possible value to represent the individual’s response to the underlying latent variable. The domain index of the latent variable for an individual response was calculated using the mathematical formula for the IAR score as \(f( x ) = \left\{ {\mathop \sum \limits_{i = 1}^{n} \left( {x_{ri} {|}x_{hi} } \right)} \right\}/n = \left\{ {\left( {x_{r1} {|}x_{h1} } \right) + \left( {x_{r2} {|}x_{h2} } \right) + \ldots \ldots \left( {x_{rn} {|}x_{hn} } \right)} \right\}/n,\) a generalized form of the RS score for an individual response published previously. A household survey found a 46% knowledge rate about organ donation by RS score, indicating 23% bias in the systematic review, having a pooled sample of 6697 individuals from the same region. The study showed that IAR methodology can empower researchers to leverage qualitative responses effectively, broadening the applicability of advanced statistical tools in qualitative research paradigms.