The Cortisol Assessment List (CoAL) A tool to systematically document and evaluate cortisol assessment in blood, urine and saliva.

BACKGROUND

The reliable assessment of cortisol is a necessary requirement to produce replicable research. Several recommendations to increase cortisol assessment reliability exist. However, cortisol assessment methodology is still rather heterogeneous. For this reason, the Cortisol Assessment List (CoAL) was created.The CoAL can be used to guide researchers during the planning phase and document which measures were taken to increase cortisol data reliability in original studies. Moreover, the CoAL can be used to evaluate data quality in meta research. The items representing strategies to obtain reliable cortisol data can be weighted to indicate which are absolutely necessary to consider and which could be applied less restrictively in order to balance data quality and feasibility. In this paper, the construction process of the CoAL is described.

METHODS

Item synthesis of the CoAL included a literature search to extract empirically based suggestions regarding the reliable assessment of cortisol. Estimates for the item weighting system were obtained by inviting experts in the field to participate in an online survey (n = 25). Inter-rater reliability (IRR) of the CoAL, was determined by letting independent raters use the CoAL to evaluate a set of randomly selected original studies (k = 90).

RESULTS

The CoAL was divided into four subscales related to the the consideration of and . Survey results indicated high agreement among experts for most items (89%) with approximately half of the items in the CoAL being classified as (Cortisol Awakening Response (CAR): 52%; basal cortisol: 52%; reactive cortisol: 44%) in order to obtain reliable cortisol data. Inter-rater agreement was very high (Cohen's Kappa = .98 - 0.99), indicating sufficient psychometric quality of the CoAL.

DISCUSSION

The CoAL is the first tool to systematically plan, document and evaluate cortisol assessment. The survey results indicate that the majority of respondents are aware of essential requirements to increase data reliability. However, results were heterogeneous for some items, highlighting the need to start a process of developing a broad scientific consensus regarding reliable cortisol assessment. The implementation of the CoAL could be a first step in this direction. In conclusion, the CoAL reflects empirical evidence and expert knowledge regarding cortisol assessment and can be used as a flexible tool to plan and document empirical studies or evaluate cortisol data quality in meta research.