The following information was collected: a description of the instrument, including domains and attribute levels of health, target population and target health outcome, a description of reliability and validity testing, and scoring system, if available.
Using a discrete choice experiment (DCE), we explored community preferences for the attributes and attribute-levels of a prospective MHI scheme, aimed at filling health coverage gaps in Malawi.
Since this was not a feasible number of scenarios for participants to complete, an efficient fractional factorial design was used, based on the number of attributes and attribute levels, to select a subset of comparisons from the full list.
In conducting our DCE, we first set out to identify a common set of relevant attributes and attribute-levels for different modes of drug administration.
Our study aimed at filling this gap by documenting a rigorous process of developing attributes and attribute-levels for the design of a DCE, to elicit community preferences for a potential MHI product in rural Malawi.
This paper responds to such calls by carefully reporting a systematic process of developing micro health insurance attributes and attribute-levels for the design of a DCE in rural Malawi.
Lastly, integration of qualitative approaches throughout the study process, including in the establishment of attributes and attribute levels and generation of the questionnaire and consultation processes to obtain a deeper understanding of the study results, is increasingly recognized as important in DCE studies [ 12, 33].
Conducting a DCE involves the following steps: (i) identification of the attributes and attribute levels, (ii) experimental design of the choice sets, (iii) questionnaire development, (iv) study sample and (v) data analysis.
The attributes and the attribute levels of these treatment alternatives were derived from the literature (Stanford et al, 2000; Potosky et al, 2004; Damber and Khatami, 2005; Korfage et al, 2005; Penson et al, 2008).
In this study, we provide an initial examination of the responsiveness of each tissue to mTORC2 inhibition and attribute the levels of FKBP12 and FKBP51 as determining factors for this responsiveness.
