Exploring judgement and decision making noise in arboricultural risk assessment: What information do people use when making risk judgements, how does this influence decisions, and is this consistent across practitioners?

Project Description

Aim: To explore the effect of “noise” on judgements that underpin tree risk assessment and how these affect decisions, to inform the development of a holistic tree risk assessment tool/measure/guideline (format will be dependent on the findings of the study).

Objectives:
(1) To understand the judgement and decision making process of practitioners when assessing tree risk.
(2) To identify what risk information practitioners use during tree risk assessment, what risk information they don’t use, and why.
(3) To identify from the findings of (2) which risk information used is known to be predictive of tree risk, and hence identify the risk information that is used which is ‘not predictive’ and therefore can be considered “noise” within the assessment.
(4) Identify whether this “noise” from (3) is actually detrimental or may be beneficial to tree risk assessment.
(5) To identify whether there is (a) consistency in the risk information used across practitioners’ risk assessments and (b) consistency in across practitioners’ decisions about risk.

The study will involve a quasi-experimental approach asking practitioners to assess risk based on three trees. Practitioners will be asked to complete a standardized risk assessment pro-form designed for the study and complete a questionnaire after their assessment of the three trees. This will provide a list of risk factors drawn from the academic evidence base which are known to be predictive and others which are not predictive of tree risk. Practitioners will provide a judgement using a rating scale on how important these factors are when they are assessing tree risk. A sub-sample of practitioners will be recruited to take [art in short one-to-one interviews (15-30 minutes) to better understand their rationale and decision making process. Findings from the study will be used to, first, answer the objectives outlined above and, second, develop a first iteration of a tree risk assessment tool/measure/guideline.